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SmartPhase Analyzer📝 SmartPhase Analyzer – Composite Market Regime Classifier SmartPhase Analyzer is an adaptive regime classification tool that scores market conditions using a customizable set of statistical indicators. It blends multiple normalized metrics into a composite score, which is dynamically evaluated against rolling statistical thresholds to determine the current market regime. ✅ Features: Composite score calculated from 13+ toggleable statistical indicators: Sharpe, Sortino, Omega, Alpha, Beta, CV, R², Entropy, Drawdown, Z-Score, PLF, SRI, and Momentum Rank Uses dynamic thresholds (mean ± std deviation) to classify regime states: 🟢 BULL – Strongly bullish 🟩 ACCUM – Mildly bullish ⚪ NEUTRAL – Sideways 🟧 DISTRIB – Mildly bearish 🔴 BEAR – Strongly bearish Color-coded histogram for composite score clarity Real-time regime label plotted on chart Benchmark-aware metrics (Alpha, Beta, etc.) Modular design using the StatMetrics library by RWCS_LTD 🧠 How to Use: Enable/disable metrics in the settings panel to customize your composite model Use the composite histogram and regime background for discretionary or systematic analysis ⚠️ Disclaimer: This indicator is for educational and informational purposes only. It does not constitute financial advice or a trading recommendation. Always consult your financial advisor before making investment decisions.
Pine Script®指標
由RWCS_LTD提供
6
StatMetricsLibrary "StatMetrics" A utility library for common statistical indicators and ratios used in technical analysis. Includes Z-Score, correlation, PLF, SRI, Sharpe, Sortino, Omega ratios, and normalization tools. zscore(src, len)   Calculates the Z-score of a series   Parameters:      src (float) : The input price or series (e.g., close)      len (simple int) : The lookback period for mean and standard deviation   Returns: Z-score: number of standard deviations the input is from the mean corr(x, y, len)   Computes Pearson correlation coefficient between two series   Parameters:      x (float) : First series      y (float) : Second series      len (simple int) : Lookback period   Returns: Correlation coefficient between -1 and 1 plf(src, longLen, shortLen, smoothLen)   Calculates the Price Lag Factor (PLF) as the difference between long and short Z-scores, normalized and smoothed   Parameters:      src (float) : Source series (e.g., close)      longLen (simple int) : Long Z-score period      shortLen (simple int) : Short Z-score period      smoothLen (simple int) : Hull MA smoothing length   Returns: Smoothed and normalized PLF oscillator sri(signal, len)   Computes the Statistical Reliability Index (SRI) based on trend persistence   Parameters:      signal (float) : A price or signal series (e.g., smoothed PLF)      len (simple int) : Lookback period for smoothing and deviation   Returns: Normalized trend reliability score sharpe(src, len)   Calculates the Sharpe Ratio over a period   Parameters:      src (float) : Price series (e.g., close)      len (simple int) : Lookback period   Returns: Sharpe ratio value sortino(src, len)   Calculates the Sortino Ratio over a period, using only downside volatility   Parameters:      src (float) : Price series      len (simple int) : Lookback period   Returns: Sortino ratio value omega(src, len)   Calculates the Omega Ratio as the ratio of upside to downside return area   Parameters:      src (float) : Price series      len (simple int) : Lookback period   Returns: Omega ratio value beta(asset, benchmark, len)   Calculates beta coefficient of asset vs benchmark using rolling covariance   Parameters:      asset (float) : Series of the asset (e.g., close)      benchmark (float) : Series of the benchmark (e.g., SPX close)      len (simple int) : Lookback window   Returns: Beta value (slope of linear regression) alpha(asset, benchmark, len)   Calculates rolling alpha of an asset relative to a benchmark   Parameters:      asset (float) : Series of the asset (e.g., close)      benchmark (float) : Series of the benchmark (e.g., SPX close)      len (simple int) : Lookback window   Returns: Alpha value (excess return not explained by Beta exposure) skew(x, len)   Computes skewness of a return series   Parameters:      x (float) : Input series (e.g., returns)      len (simple int) : Lookback period   Returns: Skewness value kurtosis(x, len)   Computes kurtosis of a return series   Parameters:      x (float) : Input series (e.g., returns)      len (simple int) : Lookback period   Returns: Kurtosis value cv(x, len)   Calculates Coefficient of Variation   Parameters:      x (float) : Input series (e.g., returns or prices)      len (simple int) : Lookback period   Returns: CV value autocorr(x, len)   Calculates autocorrelation with 1-lag   Parameters:      x (float) : Series to test      len (simple int) : Lookback window   Returns: Autocorrelation at lag 1 stderr(x, len)   Calculates rolling standard error of a series   Parameters:      x (float) : Input series      len (simple int) : Lookback window   Returns: Standard error (std dev / sqrt(n)) info_ratio(asset, benchmark, len)   Calculates the Information Ratio   Parameters:      asset (float) : Asset price series      benchmark (float) : Benchmark price series      len (simple int) : Lookback period   Returns: Information ratio (alpha / tracking error) tracking_error(asset, benchmark, len)   Measures deviation from benchmark (Tracking Error)   Parameters:      asset (float) : Asset return series      benchmark (float) : Benchmark return series      len (simple int) : Lookback window   Returns: Tracking error value max_drawdown(x, len)   Computes maximum drawdown over a rolling window   Parameters:      x (float) : Price series      len (simple int) : Lookback window   Returns: Rolling max drawdown percentage (as a negative value) zscore_signal(z, ob, os)   Converts Z-score into a 3-level signal   Parameters:      z (float) : Z-score series      ob (float) : Overbought threshold      os (float) : Oversold threshold   Returns: -1, 0, or 1 depending on signal state r_squared(x, y, len)   Calculates rolling R-squared (coefficient of determination)   Parameters:      x (float) : Asset returns      y (float) : Benchmark returns      len (simple int) : Lookback window   Returns: R-squared value (0 to 1) entropy(x, len)   Approximates Shannon entropy using log returns   Parameters:      x (float) : Price series      len (simple int) : Lookback period   Returns: Approximate entropy zreversal(z)   Detects Z-score reversals to the mean   Parameters:      z (float) : Z-score series   Returns: +1 on upward reversal, -1 on downward momentum_rank(x, len)   Calculates relative momentum strength   Parameters:      x (float) : Price series      len (simple int) : Lookback window   Returns: Proportion of lookback where current price is higher normalize(x, len)   Normalizes a series to a 0–1 range over a period   Parameters:      x (float) : The input series      len (simple int) : Lookback period   Returns: Normalized value between 0 and 1 composite_score(score1, score2, score3)   Combines multiple normalized scores into a composite score   Parameters:      score1 (float)      score2 (float)      score3 (float)   Returns: Average composite score
Pine Script®腳本庫
由RWCS_LTD提供
TitanGrid L/S SuperEngineTitanGrid L/S SuperEngine Experimental Trend-Aligned Grid Signal Engine for Long & Short Execution 🔹 Overview TitanGrid is an advanced, real-time signal engine built around a tactical grid structure. It manages Long and Short trades using trend-aligned entries, layered scaling, and partial exits. Unlike traditional strategy() -based scripts, TitanGrid runs as an indicator() , but includes its own full internal simulation engine. This allows it to track capital, equity, PnL, risk exposure, and trade performance bar-by-bar — effectively simulating a custom backtest, while remaining compatible with real-time alert-based execution systems. The concept was born from the fusion of two prior systems: Assassin’s Grid (grid-based execution and structure) + Super 8 (trend-filtering, smart capital logic), both developed under the AssassinsGrid framework. 🔹 Disclaimer This is an experimental tool intended for research, testing, and educational use. It does not provide guaranteed outcomes and should not be interpreted as financial advice. Use with demo or simulated accounts before considering live deployment. 🔹 Execution Logic Trend direction is filtered through a custom SuperTrend engine. Once confirmed: • Long entries trigger on pullbacks, exiting progressively as price moves up • Short entries trigger on rallies, exiting as price declines Grid levels are spaced by configurable percentage width, and entries scale dynamically. 🔹 Stop Loss Mechanism TitanGrid uses a dual-layer stop system: • A static stop per entry, placed at a fixed percentage distance matching the grid width • A trend reversal exit that closes the entire position if price crosses the SuperTrend in the opposite direction Stops are triggered once per cycle, ensuring predictable and capital-aware behavior. 🔹 Key Features • Dual-side grid logic (Long-only, Short-only, or Both) • SuperTrend filtering to enforce directional bias • Adjustable grid spacing, scaling, and sizing • Static and dynamic stop-loss logic • Partial exits and reset conditions • Webhook-ready alerts (browser-based automation compatible) • Internal simulation of equity, PnL, fees, and liquidation levels • Real-time dashboard for full transparency 🔹 Best Use Cases TitanGrid performs best in structured or mean-reverting environments. It is especially well-suited to assets with the behavioral profile of ETH — reactive, trend-intraday, and prone to clean pullback formations. While adaptable to multiple timeframes, it shows strongest performance on the 15-minute chart , offering a balance of signal frequency and directional clarity. 🔹 License Published under the Mozilla Public License 2.0 . You are free to study, adapt, and extend this script. 🔹 Panel Reference The real-time dashboard displays performance metrics, capital state, and position behavior: • Asset Type – Automatically detects the instrument class (e.g., Crypto, Stock, Forex) from symbol metadata • Equity – Total simulated capital: realized PnL + floating PnL + remaining cash • Available Cash – Capital not currently allocated to any position • Used Margin – Capital locked in open trades, based on position size and leverage • Net Profit – Realized gain/loss after commissions and fees • Raw Net Profit – Gross result before trading costs • Floating PnL – Unrealized profit or loss from active positions • ROI – Return on initial capital, including realized and floating PnL. Leverage directly impacts this metric, amplifying both gains and losses relative to account size. • Long/Short Size & Avg Price – Open position sizes and volume-weighted average entry prices • Leverage & Liquidation – Simulated effective leverage and projected liquidation level • Hold – Best-performing hold side (Long or Short) over the session • Hold Efficiency – Performance efficiency during holding phases, relative to capital used • Profit Factor – Ratio of gross profits to gross losses (realized) • Payoff Ratio – Average profit per win / average loss per loss • Win Rate – Percent of profitable closes (including partial exits) • Expectancy – Net average result per closed trade • Max Drawdown – Largest recorded drop in equity during the session • Commission Paid – Simulated trading costs: maker, taker, funding • Long / Short Trades – Count of entry signals per side • Time Trading – Number of bars spent in active positions • Volume / Month – Extrapolated 30-day trading volume estimate • Min Capital – Lowest equity level recorded during the session 🔹 Reference Ranges by Strategy Type Use the following metrics as reference depending on the trading style: Grid / Mean Reversion • Profit Factor: 1.2 – 2.0 • Payoff Ratio: 0.5 – 1.2 • Win Rate: 50% – 70% (based on partial exits) • Expectancy: 0.05% – 0.25% • Drawdown: Moderate to high • Commission Impact: High Trend-Following • Profit Factor: 1.5 – 3.0 • Payoff Ratio: 1.5 – 3.5 • Win Rate: 30% – 50% • Expectancy: 0.3% – 1.0% • Drawdown: Low to moderate Scalping / High-Frequency • Profit Factor: 1.1 – 1.6 • Payoff Ratio: 0.3 – 0.8 • Win Rate: 80% – 95% • Expectancy: 0.01% – 0.05% • Volume / Month: Very high Breakout Strategies • Profit Factor: 1.4 – 2.2 • Payoff Ratio: 1.2 – 2.0 • Win Rate: 35% – 60% • Expectancy: 0.2% – 0.6% • Drawdown: Can be sharp after failed breakouts 🔹 Note on Performance Simulation TitanGrid includes internal accounting of fees, slippage, and funding costs. While its logic is designed for precision and capital efficiency, performance is naturally affected by exchange commissions. In frictionless environments (e.g., zero-fee simulation), its high-frequency logic could — in theory — extract substantial micro-edges from the market. However, real-world conditions introduce limits, and all results should be interpreted accordingly.
Pine Script®指標
由AssassinsGrid提供
4
Candle Range % vs 8-Candle AvgCandle % Indicator – Measure Candle Strength by Range % **Overview:** The *Candle % Indicator* helps traders visually and analytically gauge the strength or significance of a price candle relative to its recent historical context. This is particularly useful for detecting breakout moves, volatility shifts, or overextended candles that may signal exhaustion. **What It Does:** * Calculates the **percentage range** of the current candle compared to the **average range of the past N candles**. * Highlights candles that exceed a user-defined threshold (e.g., 150% of the average range). * Useful for **filtering out extreme candles** that might represent anomalies or unsustainable moves. * Can be combined with other strategies (like EMA crossovers, support/resistance breaks, etc.) to improve signal quality. **Use Case Examples:** ***Filter out fakeouts** in breakout strategies by ignoring candles that are overly large and may revert. ***Volatility control**: Avoid entries when market conditions are erratic. **Confluence**: Combine with EMA or RSI signals for refined entries. **How to Read:** * If a candle is larger than the average range by more than the set percentage (default 150%), it's flagged (e.g., no entry signal or optional visual marker). * Ideal for intraday, swing, or algorithmic trading setups. **Customizable Inputs:** **Lookback Period**: Number of previous candles to calculate the average range. **% Threshold**: Maximum percentage a candle can exceed the average before being filtered or marked.
Pine Script®指標
由nckvsssy79提供
ALEX - ATR Extensions + ADR + TableALEX - ATR Extensions + ADR + Table Overview The ALEX ATR Extensions indicator is a comprehensive volatility and momentum analysis tool that combines Average True Range (ATR), Average Daily Range (ADR), and moving average distance calculations in a single, customizable display. This indicator helps traders assess current price action relative to historical volatility and key moving averages, providing crucial context for risk management and trade planning. Key Features Multi-Metric Analysis - ATR Percentage: Current ATR as a percentage of price for volatility assessment - ADR Percentage: Average Daily Range as a percentage for typical daily movement - Low of Day Distance: Distance from current price to daily low - Moving Average Distance: ATR-normalized distance from 21 and 50 period moving averages Flexible Moving Average Options - Configurable MA Types: Choose between EMA or SMA for both 21 and 50 period averages - Customizable Periods: Adjust moving average lengths to suit your trading style - Daily Timeframe Data: Uses daily moving averages regardless of chart timeframe ATR Extension Levels - Dynamic Price Targets: Calculate extension levels based on ATR multiples from moving averages - Visual Reference Lines: Optional overlay lines showing ATR extension targets - Customizable Multipliers: Adjust ATR multipliers for different risk/reward scenarios Smart Visual Alerts - Color-Coded Distance Metrics: Automatic color changes based on distance thresholds - Symbol Plotting: Customizable chart symbols when distance thresholds are exceeded - Threshold-Based Alerts: Visual cues when price reaches significant ATR distances Comprehensive Data Table - Real-Time Metrics: Live updating table with all key measurements - Customizable Display: Toggle individual metrics on/off based on preference - Professional Styling: Adjustable colors, fonts, and transparency How to Use Volatility Assessment - High ATR%: Indicates elevated volatility, larger position sizing considerations - Low ATR%: Suggests compressed volatility, potential for expansion - ADR% Comparison: Compare current day's range to historical average Moving Average Analysis - ATR Distance 21/50: Normalized distance showing how extended price is from key levels - Positive Values: Price above moving average (bullish positioning) - Negative Values: Price below moving average (bearish positioning) - Color Changes: Automatic alerts when reaching threshold levels Extension Target Planning - ATR Extension Lines: Visual price targets based on volatility-adjusted projections - Risk/Reward Planning: Use extension levels for profit target placement - Breakout Confirmation: Extension levels can confirm breakout validity Symbol Alert System - Chart Symbols: Automatic plotting when distance thresholds are breached - Customizable Triggers: Set your own threshold levels for alerts - Visual Scanning: Quick identification of extended conditions across multiple charts Settings Display Controls - Show ADR%: Toggle average daily range percentage display - Show ATR%: Toggle average true range percentage display - Show LoD Distance: Toggle low of day distance calculation - Show LoD Price: Toggle actual low of day price display - Show ATR Distance from 21/50 DMA: Toggle moving average distance metrics - Show 21/50 DMA Price: Toggle actual moving average price display - Show ATR Extension Levels: Toggle extension target display in table Moving Average Configuration - 21/50 DMA Type: Choose between EMA or SMA calculation methods - 21/50 DMA Period: Customize moving average lengths - ADR/ATR Length: Adjust calculation periods for range measurements Color Thresholds - Threshold Levels: Set distance levels for color changes (default 2.0 and 5.0) - Custom Colors: Choose colors for different threshold breaches - Separate 21/50 Settings: Independent color schemes for each moving average Symbol Settings - Show Char Symbol: Toggle symbol plotting for each moving average - Custom Symbols: Choose any character for chart plotting - Symbol Colors: Customize colors for visual distinction - Threshold Levels: Set trigger points for symbol appearance ATR Extension Lines - Show Extension Lines: Toggle visual extension level lines - ATR Multipliers: Customize extension distance (default 2.0x) - Line Colors: Choose colors for extension level visualization Table Customization - Background Color: Adjust table transparency and color - Text Color: Customize default text appearance - Font Size: Choose from tiny to huge font options Advanced Applications Trend Strength Analysis - Large ATR distances suggest strong trending moves - Small ATR distances indicate potential consolidation or reversal zones - Compare current readings to recent historical ranges Risk Management - Use ATR% for position sizing calculations - Extension levels provide natural profit target zones - Distance metrics help identify overextended conditions Multi-Timeframe Context - Apply to different timeframes for comprehensive analysis - Daily data provides consistency across all chart intervals - Combine with weekly/monthly analysis for broader context Market Regime Identification - High volatility periods: Increased ATR% readings - Low volatility periods: Compressed ATR% readings - Trending markets: Sustained high distance readings - Consolidating markets: Low distance readings with frequent color changes Best Practices Volatility-Adjusted Trading - Increase position sizes during low volatility periods - Reduce position sizes during high volatility periods - Use ATR% for stop-loss placement relative to normal market movement Extension Level Usage - Primary targets: 1.5-2.0x ATR extensions - Secondary targets: 2.5-3.0x ATR extensions - Avoid chasing prices beyond 3x ATR extensions Threshold Optimization - Backtest different threshold levels for your trading style - Consider market conditions when setting alert levels - Adjust thresholds based on instrument volatility characteristics Integration Strategies - Combine with momentum indicators for confirmation - Use alongside support/resistance levels - Incorporate into systematic trading approaches Technical Specifications - Compatible with Pine Script v6 - Uses daily timeframe data for consistency - Optimized for real-time performance - Works on all chart types and timeframes - Supports all tradeable instruments Ideal For - Swing traders using daily charts - Position traders seeking volatility context - Day traders needing intraday reference levels - Risk managers requiring volatility metrics - Systematic traders building rule-based strategies Disclaimer This indicator is for educational and informational purposes only. It should not be used as the sole basis for trading decisions. Always combine with other forms of analysis, proper risk management techniques, and consider your individual trading plan and risk tolerance. Past performance does not guarantee future results. Compatible with Pine Script v6 | Optimized for daily timeframe analysis | Works across all markets and instruments
Pine Script®指標
由Alex_PrimeTrading提供
21DMA Structure Counter (EMA/SMA Option)21DMA Structure Counter (EMA/SMA Option) Overview The 21DMA Structure Counter is an advanced technical indicator that tracks consecutive periods where price action remains above a 21-period moving average structure. This indicator helps traders identify momentum phases and potential trend exhaustion points using statistical analysis. Key Features Moving Average Structure - Configurable MA Type: Choose between EMA (Exponential Moving Average) or SMA (Simple Moving Average) - 21-Period Default: Optimized for the widely-watched 21-period moving average - Triple MA Structure: Tracks high, close, and low moving averages for comprehensive analysis Statistical Analysis - Cycle Counting: Automatically counts consecutive periods above the MA structure - Historical Data: Maintains up to 2,500 historical cycles (approximately 10 years of daily data) - Z-Score Calculation: Provides statistical context using mean and standard deviation - Multiple Standard Deviation Levels: Displays +1, +2, and +3 standard deviation thresholds Visual Indicators Color-Coded Bars: - Gray: Below 10-year average - Yellow: Between average and +1 standard deviation - Orange: Between +1 and +2 standard deviations - Red: Between +2 and +3 standard deviations - Fuchsia: Above +3 standard deviations (extreme readings) Breadth Integration - Multiple Breadth Options: NDFI, NDTH, NDTW (NASDAQ breadth indicators), or VIX - Background Shading: Visual alerts when breadth reaches extreme levels - High/Low Thresholds: Customizable levels for breadth analysis - Real-time Display: Current breadth value shown in data table Smart Reset Logic - High Below Structure Reset: Automatically resets count when daily high falls below the lowest MA - Flexible Hold Period: Continues counting during temporary weakness as long as structure isn't violated - Precise Entry/Exit: Strict criteria for starting cycles, flexible for maintaining them How to Use Trend Identification - Rising Counts: Indicate sustained momentum above key moving average structure - Extreme Readings: Z-scores above +2 or +3 suggest potential trend exhaustion - Historical Context: Compare current cycles to 10-year statistical averages Risk Management - Breadth Confirmation: Use breadth shading to confirm market-wide strength/weakness - Statistical Extremes: Exercise caution when readings reach +3 standard deviations - Reset Signals: Pay attention to structure violations for potential trend changes Multi-Timeframe Application - Daily Charts: Primary timeframe for swing trading and position management - Weekly/Monthly: Longer-term trend analysis - Intraday: Shorter-term momentum assessment (adjust MA period accordingly) Settings Moving Average Options - Type: EMA or SMA selection - Period: Default 21 (customizable) - Reset Days: Days below structure required for reset Visual Customization - Standard Deviation Lines: Toggle and customize colors for +1, +2, +3 SD - Breadth Selection: Choose from NDFI, NDTH, NDTW, or VIX - Threshold Levels: Set custom high/low breadth thresholds - Table Styling: Customize text colors, background, and font size Technical Notes - Data Retention: Maintains 2,500 historical cycles for robust statistical analysis - Real-time Updates: Calculations update with each new bar - Breadth Integration: Uses security() function to pull external breadth data - Performance Optimized: Efficient array management prevents memory issues Best Practices 1. Combine with Price Action: Use alongside support/resistance and chart patterns 2. Monitor Breadth Divergences: Watch for breadth weakness during strong readings 3. Respect Statistical Extremes: Exercise caution at +2/+3 standard deviation levels 4. Context Matters: Consider overall market environment and sector rotation 5. Risk Management: Use appropriate position sizing, especially at extreme readings Disclaimer This indicator is for educational and informational purposes only. It should not be used as the sole basis for trading decisions. Always combine with other forms of analysis and proper risk management techniques. Compatible with Pine Script v6 | Optimized for daily timeframes | Best used on major indices and liquid stocks
Pine Script®指標
由Alex_PrimeTrading提供
Pair TradingPAIR TRADING Description: This indicator is a simple and intuitive tool for rotating between two assets based on their relative price ratio. By comparing the prices of Asset A and Asset B, it plots a “ratio line” (gray) with dynamic upper and lower boundaries (red and blue). When the ratio reaches the red line, Asset A is expensive → rotate out of A and into B. When the ratio touches the blue line, Asset A is cheap → rotate back into A. The chart also shows: 🔹 Background highlights for visual cues 🔹 “Rotate to A” or “Rotate to B” markers for easy decisions 🔹 A live summary table with mean ratio, upper/lower boundaries, and current ratio How to Use: Select Asset A and Asset B in the settings. Adjust the Lookback Period and Threshold if needed. Watch the gray ratio line as it moves: Above red line? → Consider rotating into B Below blue line? → Consider rotating into A Use the background color changes and rotation labels to spot clear rotation opportunities! Why Pair Trading? Pair trading is a powerful way to manage a portfolio because it neutralizes market direction risk and focuses on relative value. By rotating between correlated assets, you can: Smooth out returns Avoid holding a weak asset too long Capture reversion when assets diverge too far This approach can enhance risk-adjusted returns and help keep your portfolio balanced and nimble! How to Pick Pairs: Choose assets with strong correlation or similar drivers. Look for common trends (sector, macro). Start with assets you know best (high-conviction ideas). Make sure both have good liquidity for reliable trading! TO HELP FIND CORRELATED ASSETS: Use the Correlation Coefficient indicator in TradingView: Click Indicators Search for “Correlation Coefficient” Add it to your chart Input the symbol of the second asset (e.g., if you’re on MSTR, input TSLA). This plots the rolling correlation coefficient — super helpful! Pair trading can turn big swings into steady rotations and help you stay active even when the market is choppy. It’s a simple, practical approach to keep your portfolio balanced.
Pine Script®指標
由renderingnature1提供
P&L Entry Zone Marker (clean)This indicator is a simple visual calculator for futures traders. It helps you track your long and short entry zones based on position size and average price. 🔹 Green line – recalculated long entry after averaging down. 🔹 Red line – short entry point. You can manually input your initial entry, volume, averaging volume, and averaging price. The script calculates your new average entry for long positions and plots both lines as full horizontal levels across the chart. ✳️ Useful for: Visualizing break-even zones Planning P&L zones for hedged positions Quickly aligning your trades with market structure ✅ Clean version — no labels, just lines. 📉 Works on all symbols and timeframes.
Pine Script®指標
由oleksandrgridin提供
Yearly Performance Table with CAGROverview This Pine Script indicator provides a clear table displaying the annual performance of an asset, along with two different average metrics: the arithmetic mean and the geometric mean (CAGR). Core Features Annual Performance Calculation: Automatically detects the first trading day of each calendar year. Calculates the percentage return for each full calendar year. Based on closing prices from the first to the last trading day of the respective year. Flexible Display: Adjustable Period: Displays data for 1-50 years (default: 10 years). Daily Timeframe Only: Functions exclusively on daily charts. Automatic Update: Always shows the latest available years. Two Average Metrics: AVG (Arithmetic Mean) A simple average of all annual returns. (Formula: (R₁ + R₂ + ... + Rₙ) ÷ n) Important: Can be misleading in the presence of volatile returns. GEO (Geometric Mean / CAGR) Compound Annual Growth Rate. (Formula: ^(1/n) - 1) Represents the true average annual growth rate. Fully accounts for the compounding effect. Limitations Daily Charts Only: Does not work on intraday or weekly/monthly timeframes. Calendar Year Basis: Calculations are based on calendar years, not rolling 12-month periods. Historical Data: Dependent on the availability of historical data from the broker/data provider. Interpretation of Results CAGR as Benchmark: The geometric mean is more suitable for performance comparisons. Annual Patterns: Individual year figures can reveal seasonal or cyclical trends.
Pine Script®指標
由robinzawa提供
Bilateral Filter For Loop [BackQuant]Bilateral Filter For Loop The Bilateral Filter For Loop is an advanced technical indicator designed to filter out market noise and smooth out price data, thus improving the identification of underlying market trends. It employs a bilateral filter, which is a sophisticated non-linear filter commonly used in image processing and price time series analysis. By considering both spatial and range differences between price points, this filter is highly effective at preserving significant trends while reducing random fluctuations, ultimately making it suitable for dynamic trend-following strategies. Please take the time to read the following: Key Features 1. Bilateral Filter Calculation: The bilateral filter is the core of this indicator and works by applying a weight to each data point based on two factors: spatial distance and price range difference. This dual weighting process allows the filter to preserve important price movements while reducing the impact of less relevant fluctuations. The filter uses two primary parameters: Spatial Sigma (σ_d): This parameter adjusts the weight applied based on the distance of each price point from the current price. A larger spatial sigma means more smoothing, as further away values will contribute more heavily to the result. Range Sigma (σ_r): This parameter controls how much weight is applied based on the difference in price values. Larger price differences result in smaller weights, while similar price values result in larger weights, thereby preserving the trend while filtering out noise. The output of this filter is a smoothed version of the original price series, which eliminates short-term fluctuations, helping traders focus on longer-term trends. The bilateral filter is applied over a rolling window, adjusting the level of smoothing dynamically based on both the distance between values and their relative price movements. 2. For Loop Calculation for Trend Scoring: A for-loop is used to calculate the trend score based on the filtered price data. The loop compares the current value to previous values within the specified window, scoring the trend as follows: +1 for upward movement (when the filtered value is greater than the previous value). -1 for downward movement (when the filtered value is less than the previous value). The cumulative result of this loop gives a continuous trend score, which serves as a directional indicator for the market's momentum. By summing the scores over the window period, the loop provides an aggregate value that reflects the overall trend strength. This score helps determine whether the market is experiencing a strong uptrend, downtrend, or sideways movement. 3. Long and Short Conditions: Once the trend score has been calculated, it is compared against predefined threshold levels: A long signal is generated when the trend score exceeds the upper threshold, indicating that the market is in a strong uptrend. A short signal is generated when the trend score crosses below the lower threshold, signaling a potential downtrend or trend reversal. These conditions provide clear signals for potential entry points, and the color-coding helps traders quickly identify market direction: Long signals are displayed in green. Short signals are displayed in red. These signals are designed to provide high-confidence entries for trend-following strategies, helping traders capture profitable movements in the market. 4. Trend Background and Bar Coloring: The script offers customizable visual settings to enhance the clarity of the trend signals. Traders can choose to: Color the bars based on the trend direction: Bars are colored green for long signals and red for short signals. Change the background color to provide additional context: The background will be shaded green for a bullish trend and red for a bearish trend. This visual feedback helps traders to stay aligned with the prevailing market sentiment. These features offer a quick visual reference for understanding the market's direction, making it easier for traders to identify when to enter or exit positions. 5. Threshold Lines for Visual Feedback: Threshold lines are plotted on the chart to represent the predefined long and short levels. These lines act as clear markers for when the market reaches a critical threshold, triggering a potential buy (long) or sell (short) signal. By showing these threshold lines on the chart, traders can quickly gauge the strength of the market and assess whether the trend is strong enough to warrant action. These thresholds can be adjusted based on the trader's preferences, allowing them to fine-tune the indicator for different market conditions or asset behaviors. 6. Customizable Parameters for Flexibility: The indicator offers several parameters that can be adjusted to suit individual trading preferences: Window Period (Bilateral Filter): The window size determines how many past price values are used to calculate the bilateral filter. A larger window increases smoothing, while a smaller window results in more responsive, but noisier, data. Spatial Sigma (σ_d) and Range Sigma (σ_r): These values control how sensitive the filter is to price changes and the distance between data points. Fine-tuning these parameters allows traders to adjust the degree of noise reduction applied to the price series. Threshold Levels: The upper and lower thresholds determine when the trend score crosses into long or short territory. These levels can be customized to better match the trader's risk tolerance or asset characteristics. Visual Settings: Traders can customize the appearance of the chart, including the line width of trend signals, bar colors, and background shading, to make the indicator more readable and aligned with their charting style. 7. Alerts for Trend Reversals: The indicator includes alert conditions for real-time notifications when the market crosses the defined thresholds. Traders can set alerts to be notified when: The trend score crosses the long threshold, signaling an uptrend. The trend score crosses the short threshold, signaling a downtrend. These alerts provide timely information, allowing traders to take immediate action when the market shows a significant change in direction. Final Thoughts The Bilateral Filter For Loop indicator is a robust tool for trend-following traders who wish to reduce market noise and focus on the underlying trend. By applying the bilateral filter and calculating trend scores, this indicator helps traders identify strong uptrends and downtrends, providing reliable entry signals with minimal market noise. The customizable parameters, visual feedback, and alerting system make it a versatile tool for traders seeking to improve their timing and capture profitable market movements. Thus following all of the key points here are some sample backtests on the 1D Chart Disclaimer: Backtests are based off past results, and are not indicative of the future. INDEX:BTCUSD INDEX:ETHUSD CRYPTO:SOLUSD
Pine Script®指標
由BackQuant提供
2
DCA Investment Tracker Pro [tradeviZion]DCA Investment Tracker Pro: Educational DCA Analysis Tool An educational indicator that helps analyze Dollar-Cost Averaging strategies by comparing actual performance with historical data calculations. --- 💡 Why I Created This Indicator As someone who practices Dollar-Cost Averaging, I was frustrated with constantly switching between spreadsheets, calculators, and charts just to understand how my investments were really performing. I wanted to see everything in one place - my actual performance, what I should expect based on historical data, and most importantly, visualize where my strategy could take me over the long term . What really motivated me was watching friends and family underestimate the incredible power of consistent investing. When Napoleon Bonaparte first learned about compound interest, he reportedly exclaimed "I wonder it has not swallowed the world" - and he was right! Yet most people can't visualize how their $500 monthly contributions today could become substantial wealth decades later. Traditional DCA tracking tools exist, but they share similar limitations: Require manual data entry and complex spreadsheets Use fixed assumptions that don't reflect real market behavior Can't show future projections overlaid on actual price charts Lose the visual context of what's happening in the market Make compound growth feel abstract rather than tangible I wanted to create something different - a tool that automatically analyzes real market history, detects volatility periods, and shows you both current performance AND educational projections based on historical patterns right on your TradingView charts. As Warren Buffett said: "Someone's sitting in the shade today because someone planted a tree a long time ago." This tool helps you visualize your financial tree growing over time. This isn't just another calculator - it's a visualization tool that makes the magic of compound growth impossible to ignore. --- 🎯 What This Indicator Does This educational indicator provides DCA analysis tools. Users can input investment scenarios to study: Theoretical Performance: Educational calculations based on historical return data Comparative Analysis: Study differences between actual and theoretical scenarios Historical Projections: Theoretical projections for educational analysis (not predictions) Performance Metrics: CAGR, ROI, and other analytical metrics for study Historical Analysis: Calculates historical return data for reference purposes --- 🚀 Key Features Volatility-Adjusted Historical Return Calculation Analyzes 3-20 years of actual price data for any symbol Automatically detects high-volatility stocks (meme stocks, growth stocks) Uses median returns for volatile stocks, standard CAGR for stable stocks Provides conservative estimates when extreme outlier years are detected Smart fallback to manual percentages when data insufficient Customizable Performance Dashboard Educational DCA performance analysis with compound growth calculations Customizable table sizing (Tiny to Huge text options) 9 positioning options (Top/Middle/Bottom + Left/Center/Right) Theme-adaptive colors (automatically adjusts to dark/light mode) Multiple display layout options Future Projection System Visual future growth projections Timeframe-aware calculations (Daily/Weekly/Monthly charts) 1-30 year projection options Shows projected portfolio value and total investment amounts Investment Insights Performance vs benchmark comparison ROI from initial investment tracking Monthly average return analysis Investment milestone alerts (25%, 50%, 100% gains) Contribution tracking and next milestone indicators --- 📊 Step-by-Step Setup Guide 1. Investment Settings 💰 Initial Investment: Enter your starting lump sum (e.g., $60,000) Monthly Contribution: Set your regular DCA amount (e.g., $500/month) Return Calculation: Choose "Auto (Stock History)" for real data or "Manual" for fixed % Historical Period: Select 3-20 years for auto calculations (default: 10 years) Start Year: When you began investing (e.g., 2020) Current Portfolio Value: Your actual portfolio worth today (e.g., $150,000) 2. Display Settings 📊 Table Sizes: Choose from Tiny, Small, Normal, Large, or Huge Table Positions: 9 options - Top/Middle/Bottom + Left/Center/Right Visibility Toggles: Show/hide Main Table and Stats Table independently 3. Future Projection 🔮 Enable Projections: Toggle on to see future growth visualization Projection Years: Set 1-30 years ahead for analysis Live Example - NASDAQ:META Analysis: Settings shown: $60K initial + $500/month + Auto calculation + 10-year history + 2020 start + $150K current value --- 🔬 Pine Script Code Examples Core DCA Calculations: // Calculate total invested over time months_elapsed = (year - start_year) * 12 + month - 1 total_invested = initial_investment + (monthly_contribution * months_elapsed) // Compound growth formula for initial investment theoretical_initial_growth = initial_investment * math.pow(1 + annual_return, years_elapsed) // Future Value of Annuity for monthly contributions monthly_rate = annual_return / 12 fv_contributions = monthly_contribution * ((math.pow(1 + monthly_rate, months_elapsed) - 1) / monthly_rate) // Total expected value theoretical_total = theoretical_initial_growth + fv_contributions Volatility Detection Logic: // Detect extreme years for volatility adjustment extreme_years = 0 for i = 1 to historical_years yearly_return = ((price_current / price_i_years_ago) - 1) * 100 if yearly_return > 100 or yearly_return < -50 extreme_years += 1 // Use median approach for high volatility stocks high_volatility = (extreme_years / historical_years) > 0.2 calculated_return = high_volatility ? median_of_returns : standard_cagr Performance Metrics: // Calculate key performance indicators absolute_gain = actual_value - total_invested total_return_pct = (absolute_gain / total_invested) * 100 roi_initial = ((actual_value - initial_investment) / initial_investment) * 100 cagr = (math.pow(actual_value / initial_investment, 1 / years_elapsed) - 1) * 100 --- 📊 Real-World Examples See the indicator in action across different investment types: Stable Index Investments: AMEX:SPY (SPDR S&P 500) - Shows steady compound growth with standard CAGR calculations Classic DCA success story: $60K initial + $500/month starting 2020. The indicator shows SPY's historical 10%+ returns, demonstrating how consistent broad market investing builds wealth over time. Notice the smooth theoretical growth line vs actual performance tracking. MIL:VUAA (Vanguard S&P 500 UCITS) - Shows both data limitation and solution approaches Data limitation example: VUAA shows "Manual (Auto Failed)" and "No Data" when default 10-year historical setting exceeds available data. The indicator gracefully falls back to manual percentage input while maintaining all DCA calculations and projections. MIL:VUAA (Vanguard S&P 500 UCITS) - European ETF with successful 5-year auto calculation Solution demonstration: By adjusting historical period to 5 years (matching available data), VUAA auto calculation works perfectly. Shows how users can optimize settings for newer assets. European market exposure with EUR denomination, demonstrating DCA effectiveness across different markets and currencies. NYSE:BRK.B (Berkshire Hathaway) - Quality value investment with Warren Buffett's proven track record Value investing approach: Berkshire Hathaway's legendary performance through DCA lens. The indicator demonstrates how quality companies compound wealth over decades. Lower volatility than tech stocks = standard CAGR calculations used. High-Volatility Growth Stocks: NASDAQ:NVDA (NVIDIA Corporation) - Demonstrates volatility-adjusted calculations for extreme price swings High-volatility example: NVIDIA's explosive AI boom creates extreme years that trigger volatility detection. The indicator automatically switches to "Median (High Vol): 50%" calculations for conservative projections, protecting against unrealistic future estimates based on outlier performance periods. NASDAQ:TSLA (Tesla) - Shows how 10-year analysis can stabilize volatile tech stocks Stable long-term growth: Despite Tesla's reputation for volatility, the 10-year historical analysis (34.8% CAGR) shows consistent enough performance that volatility detection doesn't trigger. Demonstrates how longer timeframes can smooth out extreme periods for more reliable projections. NASDAQ:META (Meta Platforms) - Shows stable tech stock analysis using standard CAGR calculations Tech stock with stable growth: Despite being a tech stock and experiencing the 2022 crash, META's 10-year history shows consistent enough performance (23.98% CAGR) that volatility detection doesn't trigger. The indicator uses standard CAGR calculations, demonstrating how not all tech stocks require conservative median adjustments. Notice how the indicator automatically detects high-volatility periods and switches to median-based calculations for more conservative projections, while stable investments use standard CAGR methods. --- 📈 Performance Metrics Explained Current Portfolio Value: Your actual investment worth today Expected Value: What you should have based on historical returns (Auto) or your target return (Manual) Total Invested: Your actual money invested (initial + all monthly contributions) Total Gains/Loss: Absolute dollar difference between current value and total invested Total Return %: Percentage gain/loss on your total invested amount ROI from Initial Investment: How your starting lump sum has performed CAGR: Compound Annual Growth Rate of your initial investment (Note: This shows initial investment performance, not full DCA strategy) vs Benchmark: How you're performing compared to the expected returns --- ⚠️ Important Notes & Limitations Data Requirements: Auto mode requires sufficient historical data (minimum 3 years recommended) CAGR Limitation: CAGR calculation is based on initial investment growth only, not the complete DCA strategy Projection Accuracy: Future projections are theoretical and based on historical returns - actual results may vary Timeframe Support: Works ONLY on Daily (1D), Weekly (1W), and Monthly (1M) charts - no other timeframes supported Update Frequency: Update "Current Portfolio Value" regularly for accurate tracking --- 📚 Educational Use & Disclaimer This analysis tool can be applied to various stock and ETF charts for educational study of DCA mathematical concepts and historical performance patterns. Study Examples: Can be used with symbols like AMEX:SPY , NASDAQ:QQQ , AMEX:VTI , NASDAQ:AAPL , NASDAQ:MSFT , NASDAQ:GOOGL , NASDAQ:AMZN , NASDAQ:TSLA , NASDAQ:NVDA for learning purposes. EDUCATIONAL DISCLAIMER: This indicator is a study tool for analyzing Dollar-Cost Averaging strategies. It does not provide investment advice, trading signals, or guarantees. All calculations are theoretical examples for educational purposes only. Past performance does not predict future results. Users should conduct their own research and consult qualified financial professionals before making any investment decisions. --- © 2025 TradeVizion. All rights reserved.
Pine Script®指標
由TradeVizion提供
2
Session Status Table📌 Session Status Table Session Status Table is an indicator that displays the real-time status of the four major trading sessions: * 🇯🇵 Asia (Tokyo) * 🇬🇧 London * 🇺🇸 New York AM * 🇺🇸 New York PM It shows which sessions are currently open, how much time remains until they open or close, and optionally sends alerts in advance. 🧩 Features: * Real-time session table — shows the status of each session on the chart. * Color-coded statuses: * 🟢 Green – Session is open * 🔴 Red – Session is closed * ⚪ Gray – Weekend * Countdown timers until session open or close. * User alerts — receive a notification a custom number of minutes before a session starts. ⚙️ Customization: * Table position — fully configurable. * Session colors — customizable for open, closed, and weekend states. * Session labels — customizable with icons. * Notifications: * Enabled through TradingView's Alerts panel. * User-defined lead time before session opens. 🕒 Time Zones: All times are calculated in UTC to ensure consistency across different markets and regions, avoiding discrepancies from time zones and daylight saving time. 🚨 How to enable alerts: 1. Open the "Alerts" panel in TradingView. 2. Click "Create Alert". 3. In the condition dropdown, choose "Session Status Table". 4. Set to any alert() trigger. 5. Save — you'll be notified a set number of minutes before each session begins. ℹ️ Technical Notes: * Built with Pine Script version 6. * Logically divided into clear sections: inputs, session calculations, table rendering, and alerts. * Optimized for performance and reliability on all timeframes. Ideal for traders who use session activity in their strategies — especially in Forex, crypto, and futures markets.
Pine Script®指標
由Gleb_Cryptox提供
1
Money Risk Management with Trade Tracking Overview The Money Risk Management with Trade Tracking indicator is a powerful tool designed for traders on TradingView to simplify trade simulation and risk management. Unlike the TradingView Strategy Tester, which can be complex for beginners, this indicator provides an intuitive, beginner-friendly interface to evaluate trading strategies in a realistic manner, mirroring real-world trading conditions. Built on the foundation of open-source contributions from LuxAlgo and TCP, this indicator integrates external indicator signals, overlays take-profit (TP) and stop-loss (SL) levels, and provides detailed money management analytics. It empowers traders to visualize potential profits, losses, and risk-reward ratios, making it easier to understand the financial outcomes of their strategies. Key Features Signal Integration: Seamlessly integrates with external long and short signals from other indicators, allowing traders to overlay TP/SL levels based on their preferred strategies. Realistic Trade Simulation: Simulates trades as they would occur in real-world scenarios, accounting for initial capital, risk percentage, leverage, and compounding effects. Money Management Dashboard: Displays critical metrics such as current capital, unrealized P&L, risk amount, potential profit, risk-reward ratio, and trade status in a customizable, beginner-friendly table. TP/SL Visualization: Plots TP and SL levels on the chart with customizable styles (solid, dashed, dotted) and colors, along with optional labels for clarity. Performance Tracking: Tracks total trades, win/loss counts, win rate, and profit factor, providing a clear overview of strategy performance. Liquidation Risk Alerts: Warns traders if stop-loss levels risk liquidation based on leverage settings, enhancing risk awareness. Benefits for Traders Beginner-Friendly: Simplifies the complexities of the TradingView Strategy Tester, offering an intuitive interface for new traders to simulate and evaluate trades without confusion. Real-World Insights: Helps traders understand the actual profit or loss potential of their strategies by factoring in capital, risk, and leverage, bridging the gap between theoretical backtesting and real-world execution. Enhanced Decision-Making: Provides clear, real-time analytics on risk-reward ratios, unrealized P&L, and trade performance, enabling informed trading decisions. Customizable and Flexible: Allows customization of TP/SL settings, table positions, colors, and sizes, catering to individual trader preferences. Risk Management Focus: Encourages disciplined trading by highlighting risk amounts, potential profits, and liquidation risks, fostering better financial planning. Why This Indicator Stands Out Many traders struggle to translate backtested strategy results into real-world outcomes due to the abstract nature of percentage-based profitability metrics. This indicator addresses that challenge by providing a practical, user-friendly tool that simulates trades with real-world parameters like capital, leverage, and compounding. Its open-source nature ensures accessibility, while its integration with other indicators makes it versatile for various trading styles. How to Use Add to TradingView: Copy the Pine Script code into TradingView’s Pine Editor and add it to your chart. Configure Inputs: Set your initial capital, risk percentage, leverage, and TP/SL values in the indicator settings. Select external long/short signal sources if integrating with other indicators. Monitor Dashboards: Use the Money Management and Target Dashboard tables to track trade performance and risk metrics in real time. Analyze Results: Review win rates, profit factors, and P&L to refine your trading strategy. Credits This indicator builds upon the open-source contributions of LuxAlgo and TCP , whose efforts in sharing their code have made this tool possible. Their dedication to the trading community is deeply appreciated.
Pine Script®指標
由mishy_Champ提供
1
PLR-Z For Loop🧠 Overview PLR-Z For Loop is a trend-following indicator built on the Power Law Residual Z-score model of Bitcoin price behavior. By measuring how far price deviates from a long-term power law regression and applying a custom scoring loop, this tool identifies consistent directional pressure in market structure. Designed for BTC, this indicator helps traders align with macro trends. 🧩 Key Features Power Law Residual Model: Tracks deviations of BTC price from its long-term logarithmic growth curve. Z-Score Normalization: Applies long-horizon statistical normalization (400/1460 bars) to smooth residual deviations into a usable trend signal. Loop-Based Trend Filter: Iteratively scores how often the current Z-score exceeds prior values, emphasizing trend persistence over volatility. Optional Smoothing: Toggleable exponential smoothing helps filter noise in choppier market conditions. Directional Regime Coloring: Aqua (bullish) and Red (bearish) visuals reinforce trend alignment across plots and candles. 🔍 How It Works Power Law Curve: Price is compared against a logarithmic regression model fitted to historical BTC price evolution (starting July 2010), defining structural support, resistance, and centerline levels. Residual Z-Score: The residual is calculated as the log-difference between price and the power law center. This residual is then normalized using a rolling mean (400 days) and standard deviation (1460 days) to create a long-term Z-score. Loop Scoring Logic: A loop compares the current Z-score to a configurable number of past bars. Each higher comparison adds +1, and each lower one subtracts -1. The result is a trend persistence score (z_loop) that grows with consistent directional momentum. Smoothing Option: A user-defined EMA smooths the score, if enabled, to reduce short-term signal noise. Signal Logic: Long signal when trend score exceeds long_threshold. Short signal when score drops below short_threshold. Directional State (CD): Internally manages the current market regime (1 = long, -1 = short), controlling all visual output. 🔁 Use Cases & Applications Macro Trend Alignment: Ideal for traders and analysts tracking Bitcoin’s structural momentum over long timeframes. Trend Persistence Filter: Helps confirm whether the current move is part of a sustained trend or short-lived volatility. Best Suited for BTC: Built specifically on the BNC BLX price history and Bitcoin’s power law behavior. Not designed for use with other assets. ✅ Conclusion PLR-Z For Loop reframes Bitcoin’s long-term power law model into a trend-following tool by scoring the persistence of deviations above or below fair value. It shifts the focus from valuation-based mean reversion to directional momentum, making it a valuable signal for traders seeking high-conviction participation in BTC’s broader market cycles. ⚠️ Disclaimer The content provided by this indicator is for educational and informational purposes only. Nothing herein constitutes financial or investment advice. Trading and investing involve risk, including the potential loss of capital. Always backtest and apply risk management suited to your strategy.
Pine Script®指標
由CipherDecoded提供
Last Week's APM & Daily % Move(Corrected)Last Week's Average Price Movement + Daily Percentage Move (based on NY time) This indicator accurately displays last week's Average Pip Movement (APM) consistently across all timeframes and tracks the true daily percentage move relative to that APM in a clear table in the top-right corner. Key Features: -Consistent Last Week's APM: Calculates the average pip movement from Monday to Friday of the previous trading week (based on daily wick-to-wick ranges, divided by 5). This APM value is now stable and the same across all chart timeframes. -Accurate Live Daily % Move: Tracks the maximum percentage the price has moved (either up or down) since the 5 PM New York time daily open, compared to last week's APM. The percentage holds the maximum value reached during the day and resets at the next 5 PM NY open. -NY Time Alignment: All time-based calculations are aligned with the New York time zone Pip Adjustment: Automatically adjusts for JPY pairs. ⚠️ Important: For the intended display and relevance of the daily percentage move, this indicator is best used on timeframes 4-hour and under. On Daily and Weekly timeframes, the APM display will show a message indicating this. We hope this indicator enhances your trading analysis.
Pine Script®指標
由delorean369提供
Daily ADR TableDaily ADR Table Indicator The Daily Average Daily Range (ADR) Table displays real-time volatility statistics directly on your chart. It shows both the current day's range and the historical average daily range as percentages of the current price, providing essential volatility metrics for trading decisions. The indicator tracks today's range in real-time throughout the trading session using session-based calculations to ensure accuracy. It compares this against a customizable historical average (default 20 days, adjustable from 1-500 days) to help traders assess whether current volatility is above or below normal levels. All values are displayed as percentages for easy comparison across different price levels and formatted to two decimal places for precision. The table position, text size, alignment, and colors are fully customizable with nine position options and professional default styling optimized for readability. This indicator is valuable for day traders, swing traders, and market analysts who need to quickly assess current market volatility relative to historical norms. It assists in position sizing decisions, setting stop losses, and identifying potential breakout or consolidation scenarios based on range expansion or contraction.
Pine Script®指標
由J-V-Y-E提供
ATR-InfoWHAT IT SHOWS - ATR (): Average True Range of the chosen timeframe, printed with the instrument’s native tick precision (format.mintick). - ATR % PRICE: ATR divided by the latest close, multiplied by 100 – the range as a percentage of current price. - LEN / TF: The ATR length and timeframe you selected (shown in small print). INPUTS - ATR Length (default 14) - ATR Timeframe (for example 60, D, W) - Design settings: table position, font size, colours, border EXAMPLES BTC-USD: price 67 800, ATR 2 450, ATR % 3.6 NQ E-Mini: price 18 230, ATR 355, ATR % 1.9 CL WTI: price 76.40, ATR 2.10, ATR % 2.8 EUR-USD: price 1.0860, ATR 0.0075, ATR % 0.69 USE CASES Volatility-adjusted stops: place your stop roughly one ATR beyond the entry price. Position sizing: money at risk divided by ATR gives the number of contracts or coins. Market selection: trade assets only when their ATR % sits in your preferred range. Strategy filter: trigger entries or exits only when ATR % crosses a chosen threshold. LIMITS ATR is descriptive; it does not predict future moves. Illiquid symbols may show exaggerated ATR spikes. ATR % ignores differing session lengths (24/7 crypto versus exchange-traded hours).
Pine Script®指標
由lou_fx提供
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®指標
由gorx1提供
Uptrick: Z-Trend BandsOverview Uptrick: Z-Trend Bands is a Pine Script overlay crafted to capture high-probability mean-reversion opportunities. It dynamically plots upper and lower statistical bands around an EMA baseline by converting price deviations into z-scores. Once price moves outside these bands and then reenters, the indicator verifies that momentum is genuinely reversing via an EMA-smoothed RSI slope. Signal memory ensures only one entry per momentum swing, and traders receive clear, real-time feedback through customizable bar-coloring modes, a semi-transparent fill highlighting the statistical zone, concise “Up”/“Down” labels, and a live five-metric scoring table. Introduction Markets often oscillate between trending and reverting, and simple thresholds or static envelopes frequently misfire when volatility shifts. Standard deviation quantifies how “wide” recent price moves have been, and a z-score transforms each deviation into a measure of how rare it is relative to its own history. By anchoring these bands to an exponential moving average, the script maintains a fluid statistical envelope that adapts instantly to both calm and turbulent regimes. Meanwhile, the Relative Strength Index (RSI) tracks momentum; smoothing RSI with an EMA and observing its slope filters out erratic spikes, ensuring that only genuine momentum flips—upward for longs and downward for shorts—qualify. Purpose This indicator is purpose-built for short-term mean-reversion traders operating on lower–timeframe charts. It reveals when price has strayed into the outer 5 percent of its recent range, signaling an increased likelihood of a bounce back toward fair value. Rather than firing on price alone, it demands that momentum follow suit: the smoothed RSI slope must flip in the opposite direction before any trade marker appears. This dual-filter approach dramatically reduces noise-driven, false setups. Traders then see immediate visual confirmation—bar colors that reflect the latest signal and age over time, clear entry labels, and an always-visible table of metric scores—so they can gauge both the validity and freshness of each signal at a glance. Originality and Uniqueness Uptrick: Z-Trend Bands stands apart from typical envelope or oscillator tools in four key ways. First, it employs fully normalized z-score bands, meaning ±2 always captures roughly the top and bottom 5 percent of moves, regardless of volatility regime. Second, it insists on two simultaneous conditions—price reentry into the bands and a confirming RSI slope flip—dramatically reducing whipsaw signals. Third, it uses slope-phase memory to lock out duplicate signals until momentum truly reverses again, enforcing disciplined entries. Finally, it offers four distinct bar-coloring schemes (solid reversal, fading reversal, exceeding bands, and classic heatmap) plus a dynamic scoring table, rather than a single, opaque alert, giving traders deep insight into every layer of analysis. Why Each Component Was Picked The EMA baseline was chosen for its blend of responsiveness—weighting recent price heavily—and smoothness, which filters market noise. Z-score deviation bands standardize price extremes relative to their own history, adapting automatically to shifting volatility so that “extreme” always means statistically rare. The RSI, smoothed with an EMA before slope calculation, captures true momentum shifts without the false spikes that raw RSI often produces. Slope-phase memory flags prevent repeated alerts within a single swing, curbing over-trading in choppy conditions. Bar-coloring modes provide flexible visual contexts—whether you prefer to track the latest reversal, see signal age, highlight every breakout, or view a continuous gradient—and the scoring table breaks down all five core checks for complete transparency. Features This indicator offers a suite of configurable visual and logical tools designed to make reversal signals both robust and transparent: Dynamic z-score bands that expand or contract in real time to reflect current volatility regimes, ensuring the outer ±zThreshold levels always represent statistically rare extremes. A smooth EMA baseline that weights recent price more heavily, serving as a fair-value anchor around which deviations are measured. EMA-smoothed RSI slope confirmation, which filters out erratic momentum spikes by first smoothing raw RSI and then requiring its bar-to-bar slope to flip before any signal is allowed. Slope-phase memory logic that locks out duplicate buy or sell markers until the RSI slope crosses back through zero, preventing over-trading during choppy swings. Four distinct bar-coloring modes—Reversal Solid, Reversal Fade, Exceeding Bands, Classic Heat—plus a “None” option, so traders can choose whether to highlight the latest signal, show signal age, emphasize breakout bars, or view a continuous heat gradient within the bands. A semi-transparent fill between the EMA and the upper/lower bands that visually frames the statistical zone and makes extremes immediately obvious. Concise “Up” and “Down” labels that plot exactly when price re-enters a band with confirming momentum, keeping chart clutter to a minimum. A real-time, five-metric scoring table (z-score, RSI slope, price vs. EMA, trend state, re-entry) that updates every two bars, displaying individual +1/–1/0 scores and an averaged Buy/Sell/Neutral verdict for complete transparency. Calculations Compute the fair-value EMA over fairLen bars. Subtract that EMA from current price each bar to derive the raw deviation. Over zLen bars, calculate the rolling mean and standard deviation of those deviations. Convert each deviation into a z-score by subtracting the mean and dividing by the standard deviation. Plot the upper and lower bands at ±zThreshold × standard deviation around the EMA. Calculate raw RSI over rsiLen bars, then smooth it with an EMA of length rsiEmaLen. Derive the RSI slope by taking the difference between the current and previous smoothed RSI. Detect a potential reentry when price exits one of the bands on the prior bar and re-enters on the current bar. Require that reentry coincide with an RSI slope flip (positive for a lower-band reentry, negative for an upper-band reentry). On first valid reentry per momentum swing, fire a buy or sell signal and set a memory flag; reset that flag only when the RSI slope crosses back through zero. For each bar, assign scores of +1, –1, or 0 for the z-score direction, RSI slope, price vs. EMA, trend-state, and reentry status. Average those five scores; if the result exceeds +0.1, label “Buy,” if below –0.1, label “Sell,” otherwise “Neutral.” Update bar colors, the semi-transparent fill, reversal labels, and the scoring table every two bars to reflect the latest calculations. How It Actually Works On each new candle, the EMA baseline and band widths update to reflect current volatility. The RSI is smoothed and its slope recalculated. The script then looks back one bar to see if price exited either band and forward to see if it reentered. If that reentry coincides with an appropriate RSI slope flip—and no signal has yet been generated in that swing—a concise label appears. Bar colors refresh according to your selected mode, and the scoring table updates to show which of the five conditions passed or failed, along with the overall verdict. This process repeats seamlessly at each bar, giving traders a continuous feed of disciplined, statistically filtered reversal cues. Inputs All parameters are fully user-configurable, allowing you to tailor sensitivity, lookbacks, and visuals to your trading style: EMA length (fairLen): number of bars for the fair-value EMA; higher values smooth more but lag further behind price. Z-Score lookback (zLen): window for calculating the mean and standard deviation of price deviations; longer lookbacks reduce noise but respond more slowly to new volatility. Z-Score threshold (zThreshold): number of standard deviations defining the upper and lower bands; common default is 2.0 for roughly the outer 5 percent of moves. Source (src): choice of price series (close, hl2, etc.) used for EMA, deviation, and RSI calculations. RSI length (rsiLen): period for raw RSI calculation; shorter values react faster to momentum changes but can be choppier. RSI EMA length (rsiEmaLen): period for smoothing raw RSI before taking its slope; higher values filter more noise. Bar coloring mode (colorMode): select from None, Reversal Solid, Reversal Fade, Exceeding Bands, or Classic Heat to control how bars are shaded in relation to signals and band positions. Show signals (showSignals): toggle on-chart “Up” and “Down” labels for reversal entries. Show scoring table (enableTable): toggle the display of the five-metric breakdown table. Table position (tablePos): choose which corner (Top Left, Top Right, Bottom Left, Bottom Right) hosts the scoring table. Conclusion By merging a normalized z-score framework, momentum slope confirmation, disciplined signal memory, flexible visuals, and transparent scoring into one Pine Script overlay, Uptrick: Z-Trend Bands offers a powerful yet intuitive tool for intraday mean-reversion trading. Its adaptability to real-time volatility and multi-layered filter logic deliver clear, high-confidence reversal cues without the clutter or confusion of simpler indicators. Disclaimer This indicator is provided solely for educational and informational purposes. It does not constitute financial advice. Trading involves substantial risk and may not be suitable for all investors. Past performance is not indicative of future results. Always conduct your own testing and apply careful risk management before trading live.
Pine Script®指標
由Uptrick提供
PCA Regime-Adjusted MomentumSummary The PCA Regime-Adjusted Momentum (PCA-RAM) is an advanced market analysis tool designed to provide nuanced insights into market momentum and structural stability. It moves beyond traditional indicators by using Principal Component Analysis (PCA) to deconstruct market data into its most essential patterns. The indicator provides two key pieces of information: A smoothed momentum signal based on the market's dominant underlying trend. A dynamic regime filter that gauges the stability and clarity of the market's structure, advising you when to trust or fade the momentum signals. This allows traders to not only identify potential shifts in momentum but also to understand the context and confidence behind those signals. Core Concepts & Methodology The strength of this indicator lies in its sound, data-driven methodology. 1. Principal Component Analysis (PCA) At its core, the indicator analyzes a rolling window (default 50 periods) of standardized market data (Open, High, Low, Close, and Volume). PCA is a powerful statistical technique that distills this complex, 5-dimensional data into its fundamental, uncorrelated components of variance. We focus on the First Principal Component (PC1), which represents the single most dominant pattern or "theme" driving the market's behavior in the lookback window. 2. The Momentum Signal Instead of just looking at price, we project the current market data onto this dominant underlying pattern (PC1). This gives us a raw "projection score" that measures how strongly the current bar aligns with the historically dominant market structure. This raw score is then smoothed using two an exponential moving averages (a fast and a slow line) to create a clear, actionable momentum signal, similar in concept to a MACD. 3. The Dynamic Regime Filter This is arguably the indicator's most powerful feature. It answers the question: "How clear is the current market picture?" It calculates the Market Concentration Ratio, which is the percentage of total market variance explained by PC1 alone. A high ratio indicates that the market is moving in a simple, one-dimensional way (e.g., a clear, strong trend). A low ratio indicates the market is complex, multi-dimensional, and choppy, with no single dominant theme. Crucially, this filter is dynamic. It compares the current concentration ratio to its own recent average, allowing it to adapt to any asset or timeframe. It automatically learns what "normal" and "choppy" look like for the specific chart you are viewing. How to Interpret the Indicator The indicator is displayed in a separate pane with two key visual elements: The Momentum Lines (White & Gold) White Line: The "Fast Line," representing the current momentum. Gold Line: The "Slow Line," acting as the trend confirmation. Bullish Signal: A crossover of the White Line above the Gold Line suggests a shift to positive momentum. Bearish Signal: A crossover of the White Line below the Gold Line suggests a shift to negative momentum. The Regime Filter (Purple & Dark Red Background) This is your confidence gauge. Navy Blue Background (High Concentration): The market structure is stable, simple, and trending. Momentum signals are more reliable and should be given higher priority. Dark Red Background (Low Concentration): The market structure is complex, choppy, or directionless. Momentum signals are unreliable and prone to failure or "whipsaws." This is a signal to be cautious, tighten stops, or potentially stay out of the market. Potential Trading Strategies This tool is versatile and can be used in several ways: 1. Primary Signal Strategy Condition: Wait for the background to turn Purple, confirming a stable, high-confidence regime. Entry: Take the next crossover signal from the momentum lines (White over Gold for long, White under Gold for short). Exit/Filter: Consider exiting positions or ignoring new signals when the background turns Navy. 2. As a Confirmation or Filter for Your Existing Strategy Do you have a trend-following system? Only enable its long and short signals when the PCA-RAM background is Purple. Do you have a range-trading or mean-reversion system? It might be most effective when the PCA-RAM background is Navy, indicating a lack of a clear trend. 3. Advanced Divergence Analysis Look for classic divergences between price and the momentum lines. For example, if the price is making a new high, but the Gold Line is making a lower high, it may indicate underlying weakness in the trend, even on a Purple background. This divergence signal is more powerful because it shows that the new price high is not being confirmed by the market's dominant underlying pattern.
Pine Script®指標
由marcosag90提供
Price Statistical Strategy-Z Score V 1.01 Price Statistical Strategy – Z Score V 1.01 Overview A technical breakdown of the logic and components of the “Price Statistical Strategy – Z Score V 1.01”. This script implements a smoothed Z-Score crossover mechanism applied to the closing price to detect potential statistical deviations from local price mean. The strategy operates solely on price data (close) and includes signal spacing control and momentum-based candle filters. No volume-based or trend-detection components are included. Core Methodology The strategy is built on the statistical concept of Z-Score, which quantifies how far a value (closing price) is from its recent average, normalized by standard deviation. Two moving averages of the raw Z-Score are calculated: a short-term and a long-term smoothed version. The crossover between them generates long entries and exits. Signal Conditions Entry Condition: A long position is opened when the short-term smoothed Z-Score crosses above the long-term smoothed Z-Score, and additional entry conditions are met. Exit Condition: The position is closed when the short-term Z-Score crosses below the long-term Z-Score, provided the exit conditions allow. Signal Gapping: A minimum number of bars (Bars gap between identical signals) must pass between repeated entry or exit signals to reduce noise. Momentum Filter: Entries are prevented during sequences of three or more consecutively bullish candles, and exits are prevented during three or more consecutively bearish candles. Z-Score Function The Z-Score is calculated as: Z = (Close - SMA(Close, N)) / STDEV(Close, N) Where N is the base period selected by the user. Input Parameters Enable Smoothed Z-Score Strategy Enables or disables the Z-Score strategy logic. When disabled, no trades are executed. Z-Score Base Period Defines the number of bars used to calculate the simple moving average and standard deviation for the Z-Score. This value affects how responsive the raw Z-Score is to price changes. Short-Term Smoothing Sets the smoothing window for the short-term Z-Score. Higher values produce smoother short-term signals, reducing sensitivity to short-term volatility. Long-Term Smoothing Sets the smoothing window for the long-term Z-Score, which acts as the reference line in the crossover logic. Bars gap between identical signals Minimum number of bars that must pass before another signal of the same type (entry or exit) is allowed. This helps reduce redundant or overly frequent signals. Trade Visualization Table A table positioned at the bottom-right displays live PnL for open trades: Entry Price Unrealized PnL % Text colors adapt based on whether unrealized profit is positive, negative, or neutral. Technical Notes This strategy uses only close prices — no trend indicators or volume components are applied. All calculations are based on simple moving averages and standard deviation over user-defined windows. Designed as a minimal, isolated Z-Score engine without confirmation filters or multi-factor triggers.
Pine Script®策略
由ata_sabanci提供