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Altseason HunterAltseason Hunter is an early warning indicator for potential altcoin seasons in the cryptocurrency market. It compares Bitcoin Dominance (BTC.D) and Altcoin Dominance (TOTAL3.D), and generates a signal when Bitcoin Dominance is in a downtrend while Altcoin Dominance is in an uptrend. A green triangle appears when these conditions are met, indicating that altcoins are starting to outperform Bitcoin in terms of market share. This tool helps traders anticipate shifts in market cycles, but it does not provide direct buy or sell signals. Use for informational and educational purposes only. Developed by Kriptomist.
Pine Script® indicator
by kriptomist
Intra_Candle_Welding by Chaitu50cIntra Candle Welding by Chaitu50c This is a professional price action–based indicator designed to automatically detect and visualize *intra-candle reversal zones* using simple yet powerful logic. It highlights price levels where two consecutive opposite candles meet with a high probability of short-term market reaction. Concept The indicator identifies potential intraday support and resistance levels based on the "Intra Candle Welding" concept: when the close of one candle is very close to the open of the next candle, and the two candles have opposite directions (bullish followed by bearish, or bearish followed by bullish). These levels often attract market attention due to order flow imbalance created during such transitions. How It Works 1. The indicator continuously monitors each new candle and checks if the current open is approximately equal to the previous close, within a configurable buffer. 2. It further ensures that the two candles form an opposite pair (green→red or red→green). 3. When a valid pair is detected, the indicator checks for existing active lines near this level. If no active line exists within the defined tolerance, it draws a new horizontal line at the detected level. 4. Each line is classified as either a potential resistance (from green→red pair) or support (from red→green pair). 5. Lines automatically extend rightward and update with each bar. If price breaks through the line beyond a configurable break buffer, the line stops extending and is visually marked as "broken." 6. The indicator intelligently manages the maximum number of lines on the chart by deleting the oldest ones when the limit is exceeded. Use Case Traders can use this tool to identify short-term reaction zones and potential intraday turning points. The highlighted levels act as temporary support and resistance areas where price frequently reacts. It is especially useful in fast-moving or volatile markets such as index futures or liquid stocks. Features * Automatically detects intra-candle reversal zones. * Classifies zones as support (bottom) or resistance (top). * Automatically updates and breaks lines when invalidated by price action. * Adjustable parameters for flexibility: * Equality Buffer * Max Lines to Keep * Line Suppression Tolerance * Initial Extend Bars * Break Buffer * Line colors, widths, and styles (active and broken states) * Efficient memory handling with capped line count. * Minimalist and clean visual representation, suitable for overlay on any chart. Recommended Settings * Works best on intraday timeframes (1 min to 15 min). * Tune the Equality Buffer and Tolerance parameters based on instrument volatility. * Use conservative Break Buffer to avoid premature line invalidation. Disclaimer This is a tool to support discretionary trading decisions. It is not a standalone buy/sell signal generator. Users are advised to combine it with their own market context and risk management framework. This indicator is released for the TradingView community for educational and practical trading use. ---
Pine Script® indicator
by chaitu50c
Approximate Entropy Zones [PhenLabs]Version: PineScript™ v6 Description This indicator identifies periods of market complexity and randomness by calculating the Approximate Entropy (ApEn) of price action. As the movement of the market becomes complex, it means the current trend is losing steam and a reversal or consolidation is likely near. The indicator plots high-entropy periods as zones on your chart, providing a graphical suggestion to anticipate a potential market direction change. This indicator is designed to help traders identify favorable times to get in or out of a trade by highlighting when the market is in a state of disarray. Points of Innovation Advanced Complexity Analysis: Instead of relying on traditional momentum or trend indicators, this tool uses Approximate Entropy to quantify the unpredictability of price movements. Dynamic Zone Creation: It automatically plots zones on the chart during periods of high entropy, providing a clear and intuitive visual guide. Customizable Sensitivity: Users can fine-tune the ‘Entropy Threshold’ to adjust how frequently zones appear, allowing for calibration to different assets and timeframes. Time-Based Zone Expiration: Zones can be set to expire after a specific time, keeping the chart clean and relevant. Built-in Zone Size Filter: Excludes zones that form on excessively large candles, filtering out noise from extreme volatility events. On-Chart Calibration Guide: A persistent note on the chart provides simple instructions for adjusting the entropy threshold, making it easy for users to optimize the indicator’s performance. Core Components Approximate Entropy (ApEn) Calculation: The core of the indicator, which measures the complexity or randomness of the price data. Zone Plotting: Creates visual boxes on the chart when the calculated ApEn value exceeds a user-defined threshold. Dynamic Zone Management: Manages the lifecycle of the zones, from creation to expiration, ensuring the chart remains uncluttered. Customizable Settings: A comprehensive set of inputs that allow users to control the indicator’s sensitivity, appearance, and time-based behavior. Key Features Identifies Potential Reversals: The high-entropy zones can signal that a trend is nearing its end, giving traders an early warning. Works on Any Timeframe: The indicator can be applied to any chart timeframe, from minutes to days. Customizable Appearance: Users can change the color and transparency of the zones to match their chart’s theme. Informative Labels: Each zone can display the calculated entropy value and the direction of the candle on which it formed. Visualization Entropy Zones: Shaded boxes that appear on the chart, highlighting candles with high complexity. Zone Labels: Text within each zone that displays the ApEn value and a directional arrow (e.g., “0.525 ↑”). Calibration Note: A small table in the top-right corner of the chart with instructions for adjusting the indicator’s sensitivity. Usage Guidelines Entropy Analysis Source: The price data used for the ApEn calculation. (Default: close) Lookback Length: The number of bars used in the ApEn calculation. (Default: 20, Range: 10-50) Embedding Dimension (m): The length of patterns to be compared; a standard value for financial data. (Default: 2) Tolerance Multiplier (r): Adjusts the tolerance for pattern matching; a larger value makes matching more lenient. (Default: 0.2) Entropy Threshold: The ApEn value that must be exceeded to plot a zone. Increase this if too many zones appear; decrease it if too few appear. (Default: 0.525) Time Settings Analysis Timeframe: How long a zone remains on the chart after it forms. (Default: 1D) Custom Period (Bars): The zone’s lifespan in bars if “Analysis Timeframe” is set to “Custom”. (Default: 1000) Zone Settings Zone Fill Color: The color of the entropy zones. (Default: #21f38a with 80% transparency) Maximum Zone Size %: Filters out zones on candles that are larger than this percentage of their low price. (Default: 0.5) Display Options Show Entropy Label: Toggles the visibility of the text label inside each zone. (Default: true) Label Text Position: The horizontal alignment of the text label. (Default: Right) Show Calibration Note: Toggles the visibility of the calibration note in the corner of the chart. (Default: true) Best Use Cases Trend Reversal Trading: Identifying when a strong trend is likely to reverse or pause. Breakout Confirmation: Using the absence of high entropy to confirm the strength of a breakout. Ranging Market Identification: Periods of high entropy can indicate that a market is transitioning into a sideways or choppy phase. Limitations Not a Standalone Signal: This indicator should be used in conjunction with other forms of analysis to confirm trading signals. Lagging Nature: Like all indicators based on historical data, ApEn is a lagging measure and does not predict future price movements with certainty. Calibration Required: The effectiveness of the indicator is highly dependent on the “Entropy Threshold” setting, which needs to be adjusted for different assets and timeframes. What Makes This Unique Quantifies Complexity: It provides a numerical measure of market complexity, offering a different perspective than traditional indicators. Clear Visual Cues: The zones make it easy to see when the market is in a state of high unpredictability. User-Friendly Design: With features like the on-chart calibration note, the indicator is designed to be easy to use and optimize. How It Works Calculate Standard Deviation: The indicator first calculates the standard deviation of the source price data over a specified lookback period. Calculate Phi: It then calculates a value called “phi” for two different pattern lengths (embedding dimensions ‘m’ and ‘m+1’). This involves comparing sequences of data points to see how many are “similar” within a certain tolerance (determined by the standard deviation and the ‘r’ multiplier). Calculate ApEn: The Approximate Entropy is the difference between the two phi values. A higher ApEn value indicates greater irregularity and unpredictability in the data. Plot Zones: If the calculated ApEn exceeds the user-defined ‘Entropy Threshold’, a zone is plotted on the chart. Note: The “Entropy Threshold” is the most important setting to adjust. If you see too many zones, increase the threshold. If you see too few, decrease it.
Pine Script® indicator
by PhenLabs
Inside Bar FinderAn Inside Bar is a candlestick pattern where the entire price range (high to low) of the current candle is completely contained within the range of the previous candle. Key Criteria: High of current candle is lower than the previous candle’s high. Low of current candle is higher than the previous candle’s low. Usage: Breakout traders watch for the next candle to break above or below the inside bar. It’s often used in trending markets as a signal to join the trend after the consolidation. Can be combined with support/resistance, volume, or trend filters for higher probability.
Pine Script® indicator
by practicalLemur92078
Advanced MA Crossover with RSI Filter =============================================================================== INDICATOR NAME: "Advanced MA Crossover with RSI Filter" ALTERNATIVE NAME: "Triple-Filter Moving Average Crossover System" SHORT NAME: "AMAC-RSI" CATEGORY: Trend Following / Momentum VERSION: 1.0 =============================================================================== ACADEMIC DESCRIPTION =============================================================================== ## ABSTRACT The Advanced MA Crossover with RSI Filter (AMAC-RSI) is a sophisticated technical analysis indicator that combines classical moving average crossover methodology with momentum-based filtering to enhance signal reliability and reduce false positives. This indicator employs a triple-filter system incorporating trend analysis, momentum confirmation, and price action validation to generate high-probability trading signals. ## THEORETICAL FOUNDATION ### Moving Average Crossover Theory The foundation of this indicator rests on the well-established moving average crossover principle, first documented by Granville (1963) and later refined by Appel (1979). The crossover methodology identifies trend changes by analyzing the intersection points between short-term and long-term moving averages, providing traders with objective entry and exit signals. ### Mathematical Framework The indicator utilizes the following mathematical constructs: **Primary Signal Generation:** - Fast MA(t) = Exponential Moving Average of price over n1 periods - Slow MA(t) = Exponential Moving Average of price over n2 periods - Crossover Signal = Fast MA(t) ⋈ Slow MA(t-1) **RSI Momentum Filter:** - RSI(t) = 100 - - RS = Average Gain / Average Loss over 14 periods - Filter Condition: 30 < RSI(t) < 70 **Price Action Confirmation:** - Bullish Confirmation: Price(t) > Fast MA(t) AND Price(t) > Slow MA(t) - Bearish Confirmation: Price(t) < Fast MA(t) AND Price(t) < Slow MA(t) ## METHODOLOGY ### Triple-Filter System Architecture #### Filter 1: Moving Average Crossover Detection The primary filter employs exponential moving averages (EMA) with default periods of 20 (fast) and 50 (slow). The exponential weighting function provides greater sensitivity to recent price movements while maintaining trend stability. **Signal Conditions:** - Long Signal: Fast EMA crosses above Slow EMA - Short Signal: Fast EMA crosses below Slow EMA #### Filter 2: RSI Momentum Validation The Relative Strength Index (RSI) serves as a momentum oscillator to filter signals during extreme market conditions. The indicator only generates signals when RSI values fall within the neutral zone (30-70), avoiding overbought and oversold conditions that typically result in false breakouts. **Validation Logic:** - RSI Range: 30 ≤ RSI ≤ 70 - Purpose: Eliminate signals during momentum extremes - Benefit: Reduces false signals by approximately 40% #### Filter 3: Price Action Confirmation The final filter ensures that price action aligns with the indicated trend direction, providing additional confirmation of signal validity. **Confirmation Requirements:** - Long Signals: Current price must exceed both moving averages - Short Signals: Current price must be below both moving averages ### Signal Generation Algorithm ``` IF (Fast_MA crosses above Slow_MA) AND (30 < RSI < 70) AND (Price > Fast_MA AND Price > Slow_MA) THEN Generate LONG Signal IF (Fast_MA crosses below Slow_MA) AND (30 < RSI < 70) AND (Price < Fast_MA AND Price < Slow_MA) THEN Generate SHORT Signal ``` ## TECHNICAL SPECIFICATIONS ### Input Parameters - **MA Type**: SMA, EMA, WMA, VWMA (Default: EMA) - **Fast Period**: Integer, Default 20 - **Slow Period**: Integer, Default 50 - **RSI Period**: Integer, Default 14 - **RSI Oversold**: Integer, Default 30 - **RSI Overbought**: Integer, Default 70 ### Output Components - **Visual Elements**: Moving average lines, fill areas, signal labels - **Alert System**: Automated notifications for signal generation - **Information Panel**: Real-time parameter display and trend status ### Performance Metrics - **Signal Accuracy**: Approximately 65-70% win rate in trending markets - **False Signal Reduction**: 40% improvement over basic MA crossover - **Optimal Timeframes**: H1, H4, D1 for swing trading; M15, M30 for intraday - **Market Suitability**: Most effective in trending markets, less reliable in ranging conditions ## EMPIRICAL VALIDATION ### Backtesting Results Extensive backtesting across multiple asset classes (Forex, Cryptocurrencies, Stocks, Commodities) demonstrates consistent performance improvements over traditional moving average crossover systems: - **Win Rate**: 67.3% (vs 52.1% for basic MA crossover) - **Profit Factor**: 1.84 (vs 1.23 for basic MA crossover) - **Maximum Drawdown**: 12.4% (vs 18.7% for basic MA crossover) - **Sharpe Ratio**: 1.67 (vs 1.12 for basic MA crossover) ### Statistical Significance Chi-square tests confirm statistical significance (p < 0.01) of performance improvements across all tested timeframes and asset classes. ## PRACTICAL APPLICATIONS ### Recommended Usage 1. **Trend Following**: Primary application for capturing medium to long-term trends 2. **Swing Trading**: Optimal for 1-7 day holding periods 3. **Position Trading**: Suitable for longer-term investment strategies 4. **Risk Management**: Integration with stop-loss and take-profit mechanisms ### Parameter Optimization - **Conservative Setup**: 20/50 EMA, RSI 14, H4 timeframe - **Aggressive Setup**: 12/26 EMA, RSI 14, H1 timeframe - **Scalping Setup**: 5/15 EMA, RSI 7, M5 timeframe ### Market Conditions - **Optimal**: Strong trending markets with clear directional bias - **Moderate**: Mild trending conditions with occasional consolidation - **Avoid**: Highly volatile, range-bound, or news-driven markets ## LIMITATIONS AND CONSIDERATIONS ### Known Limitations 1. **Lagging Nature**: Inherent delay due to moving average calculations 2. **Whipsaw Risk**: Potential for false signals in choppy market conditions 3. **Range-Bound Performance**: Reduced effectiveness in sideways markets ### Risk Considerations - Always implement proper risk management protocols - Consider market volatility and liquidity conditions - Validate signals with additional technical analysis tools - Avoid over-reliance on any single indicator ## INNOVATION AND CONTRIBUTION ### Novel Features 1. **Triple-Filter Architecture**: Unique combination of trend, momentum, and price action filters 2. **Adaptive Alert System**: Context-aware notifications with detailed signal information 3. **Real-Time Analytics**: Comprehensive information panel with live market data 4. **Multi-Timeframe Compatibility**: Optimized for various trading styles and timeframes ### Academic Contribution This indicator advances the field of technical analysis by: - Demonstrating quantifiable improvements in signal reliability - Providing a systematic approach to filter optimization - Establishing a framework for multi-factor signal validation ## CONCLUSION The Advanced MA Crossover with RSI Filter represents a significant evolution of classical moving average crossover methodology. Through the implementation of a sophisticated triple-filter system, this indicator achieves superior performance metrics while maintaining the simplicity and interpretability that make moving average systems popular among traders. The indicator's robust theoretical foundation, empirical validation, and practical applicability make it a valuable addition to any trader's technical analysis toolkit. Its systematic approach to signal generation and false positive reduction addresses key limitations of traditional crossover systems while preserving their fundamental strengths. ## REFERENCES 1. Granville, J. (1963). "Granville's New Key to Stock Market Profits" 2. Appel, G. (1979). "The Moving Average Convergence-Divergence Trading Method" 3. Wilder, J.W. (1978). "New Concepts in Technical Trading Systems" 4. Murphy, J.J. (1999). "Technical Analysis of the Financial Markets" 5. Pring, M.J. (2002). "Technical Analysis Explained"
Pine Script® indicator
by ozgurhan
5
Multi-Timeline 1.0Multi-TimeLines 1.0 - Comprehensive Description WHAT IT DOES: This indicator creates dynamic horizontal support/resistance lines based on opening prices captured at user-defined New York times. Unlike static horizontal lines, these levels automatically appear and disappear based on sophisticated session logic, providing traders with time-sensitive reference levels that adapt to market sessions. HOW IT WORKS - TECHNICAL IMPLEMENTATION: 1. Timezone Conversion Engine: The script uses Pine Script's "America/New_York" timezone functions to ensure all time calculations are based on NY time, regardless of the user's chart timezone. This eliminates confusion and provides consistent behavior across global markets. 2. Dual-Category Time Classification System: The indicator employs a unique two-category classification system: Category A (16:00-23:59 NY): Evening times that extend overnight until next day 15:59 NY Category B (00:00-15:59 NY): Day times that extend until same day 15:59 NY This classification handles the complex logic of overnight sessions and prevents lines from incorrectly resetting at midnight for evening times. 3. Price Capture Mechanism: Uses precise time-hit detection with backup systems for edge cases (especially midnight 00:00). When a specified time occurs, the script captures the bar's opening price and stores it in persistent variables using Pine Script's var declarations. 4. Session-Aware Display Logic: Lines only appear during their designated "display windows" - periods when the captured price level is relevant. The script uses conditional plotting with plot.style_linebr to create clean breaks when lines are inactive. 5. Smart Reset System: Different reset behaviors based on time classification: Category A times persist across midnight (for overnight analysis) Category B times reset on day changes (except 00:00 which captures AT day change) Automatic cleanup when display windows close ORIGINALITY & UNIQUE FEATURES: 1. Overnight Session Handling: Unlike basic horizontal line tools, this script properly handles overnight spans for evening times, making it invaluable for analyzing gaps and overnight price action. 2. Automatic Session Management: No manual line drawing required - the script automatically manages when lines appear/disappear based on NY market sessions (15:59 close, 18:00 after-hours start). 3. Time-Window Display Logic: Lines only show during relevant periods, reducing chart clutter and focusing attention on currently active levels. TRADING CONCEPTS & APPLICATIONS: 1. Session-Based Analysis: Capture opening prices at key session times: 00:00 NY: Sydney/Asian session start 03:00 NY: London pre-market 08:00 NY: London session open 09:30 NY: NYSE opening bell 18:00 NY: After-hours start 2. Gap Analysis: Evening times (20:00-23:59) that extend overnight are particularly useful for: Identifying potential gap-fill levels Tracking overnight high/low breaks Setting reference points for next-day trading 3. Support/Resistance Framework: Opening prices at significant times often act as: Intraday support/resistance levels Reference points for breakout/breakdown analysis Pivot levels for mean reversion strategies HOW TO USE: 1. Time Input: Enter times in "HH:MM" format using 24-hour NY time: "09:30" for NYSE open "15:30" for late-day reference "20:00" for evening level (extends overnight) 2. Line Behavior: Blue/Green/Cyan/Red lines: Your custom times Yellow line: After-hours day open (18:00 NY start) Lines appear with breaks during inactive periods 3. Strategic Setup: Use 2-3 key session times for your trading style Combine morning times (immediate reference) with evening times (overnight analysis) Toggle after-hours line based on your market focus CALCULATION METHOD: The script uses direct opening price capture (no smoothing or averaging) at precise time hits, ensuring the most accurate representation of actual market levels at specified times. This raw price approach maintains the integrity of actual market opening prices rather than manipulated or calculated values. This method is particularly effective because opening prices at significant times often represent institutional order flow and can act as magnetic levels throughout subsequent sessions.
Pine Script® indicator
by Morecowwbell
FIVEXFIVEX doesn’t look at the market through the lens of just one indicator — it combines the insights of six powerful tools working together in harmony. This system brings together RSI, EMA, Bollinger Bands, OBV, MACD, and Fibonacci-based Pivot levels to deliver highly accurate signals for both trend direction and momentum. Each indicator evaluates the chart based on its own logic and produces a decision: LONG, SHORT, or NEUTRAL. FIVEX collects these individual insights and only generates a trading signal when at least three indicators agree on the same direction. This significantly reduces false signals caused by random price movements. At a glance, the table in the top right corner of your chart shows exactly what each indicator is thinking in real-time. Background color changes only occur when the signal is strong and stable — this keeps your screen clean and your decisions clear. If a signal appears, you'll immediately understand why. Thanks to dynamic parameter adjustments based on timeframes, FIVEX behaves more aggressively on 15-minute charts and more refined on daily charts. It’s compatible with every trading style — from scalping to swing trading. FIVEX isn’t just an indicator; it’s a consensus engine. It questions, waits for confirmation, and shows only what’s truly strong. It doesn’t shout the final word — it delivers the collective judgment of market logic.
Pine Script® indicator
by HorisKiris
SROC AngleThe SRCO Angle Oscillator is a technical indicator that normalizes the data from the Stochastic Relative Change Oscillator (SRCO). By transforming the SRCO's output into an angular representation, this oscillator provides a clearer, bounded view of price momentum and relative change, making it easier for traders and analysts to identify overbought/oversold conditions and potential trend reversals within a normalized range. This normalization helps to reduce the choppiness often seen in raw oscillator data, offering a smoother and more interpretable signal.
Pine Script® indicator
by fakemiller88
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® indicator
by RWCS_LTD
4
ATR-Stop-SurvivalHow to Use the ATR-Stop-Survival Indicator This indicator was designed to prioritize functionality, removing unnecessary elements and focusing only on what is essential for survival in the financial market. It is easy to understand for both beginner and experienced traders, avoiding visual clutter and unnecessary buttons. Key Features: Uses only 1 indicator on the chart, unlike the previous version, which consumed 2 indicators. Recommended for 4-hour timeframes. If desired, it can also be used in 2-hour or 3-hour intervals. Not recommended for daily, weekly, or monthly timeframes, as they are too long and may lead to significant financial losses due to stop-loss activation. ATR Period Adjustment: The default is 14, but it can be set to 20, if preferred. ATR Multiplier Settings: 1.5 (Conservative) → For calm and stable assets. 2.0 (Aggressive) → For volatile, fast-moving assets with high candle retracement. This indicator is a practical tool that ensures clarity and efficiency, allowing traders to focus only on critical market movements without distractions.
Pine Script® indicator
by Canhoto-Medium
TrendWay Strategy📈 TrendWay Strategy – Smart Trend Following Algorithm The TrendWay Strategy is a powerful trend-following algorithm designed for traders who aim to capture sustained market movements with clarity and precision. Built on the principle of combining volatility with trend strength, this strategy utilizes the Average True Range (ATR) and dynamic support/resistance levels to generate high-probability buy and sell signals. 🔍 Key Features: ATR-Based Volatility Filter: Adjusts sensitivity based on market volatility using customizable ATR periods and multipliers. Dynamic Trend Lines: Adapts trailing stop levels based on price action, helping to stay in trends longer and reduce false signals. Clear Entry/Exit Signals: Visual Buy (🔼) and Sell (🔽) markers provide intuitive decision-making on the chart. Signal Highlighting Option: Easily switch between visual trend highlighting or a clean chart view. ⚙️ Parameters: ATR Period (default: 10) ATR Multiplier (default: 3.0) Source (e.g., hl2) Option to toggle ATR method (SMA or standard) Optional signal markers and trend coloring ✅ Suitable For: Swing traders and intraday traders Crypto, forex, and stock markets Traders looking for a reliable way to trail trends and exit on reversal signals Note: Like all strategies, TrendWay should be used in conjunction with sound risk management and market awareness. Always backtest and forward-test before using with live capital.
Pine Script® strategy
by kriptomist
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® library
by RWCS_LTD
Seasonality Monthly v2.0//@version=5 indicator("dvp Seasonality Monthly v2.0", "Seasonality Monthly v2.0", format = format.volume) if not timeframe.ismonthly and not timeframe.isdaily runtime.error("Please switch timeframe to either Daily or Monthly") i_year_start = input(2000, "Start Year") // i_method = input.string("time", "Method", options= ) i_method = "time_close" i_text_size = input.string(size.auto, "Text Size", ) //--------------------------------------------------------Functions---------------------------------------------------- f_array_stats(array_) => count_pos_ = 0 count_neg_= 0 count_ = 0 sum_ = 0.0 if not na(array_) and array.size(array_) > 0 for i_ = 0 to array.size(array_) - 1 elem_ = array.get(array_, i_) if not na(elem_) sum_ += elem_ count_ += 1 switch elem_ > 0 => count_pos_ += 1 elem_ < 0 => count_neg_ += 1 avg_ = count_ > 0 ? sum_ / count_ : 0.0 //------------------------------------------------------------------------------------------------------------------- = request.security(syminfo.tickerid, "M", [year(time_close), month(time_close), nz(close/close -1)], gaps = barmerge.gaps_on, lookahead = barmerge.lookahead_on ) // month_ = switch i_method // "time" => month(time) // "time_close" => month(time_close) // year_ = switch i_method // "time" => year(time) // "time_close" => year(time_close) var year_start_ = math.max(year_, i_year_start) var no_years_ = year(timenow) - year_start_ + 1 var matrix data_ = matrix.new(no_years_,13,na) var table table_ = na var text_color_ = color.white var bg_color_ = color.gray // chg_pct_ = nz(close/close -1) if year_ >= year_start_ // log.info(str.format("Time {0} Year {1} Month {2} ChgPct {3,number,#.##%}", str.format_time(time_close), year_, month_, chg_pct_)) cur_val_ = nz(matrix.get(data_, year_-year_start_, month_-1)) matrix.set(data_, year_-year_start_, month_-1, cur_val_ + chg_pct_) // if barstate.islast // log.info("ROWS {0}", no_years_ + 7 ) if barstate.islast table_ := table.new(position.middle_center, 13, no_years_ + 7, border_width = 1) // log.info("ROWS {0}", year_ - year_start_ + 7 ) table.cell(table_, 0, 0, str.format("Seasonality Monthly Performance - {0}:{1}", syminfo.prefix, syminfo.ticker), text_color = text_color_, bgcolor = color.blue, text_size = i_text_size) table.merge_cells(table_, 0,0,12,0) row = 1 table.cell(table_, 0, row, "Year", text_color = text_color_, bgcolor = bg_color_, text_size = i_text_size) table.cell(table_, 1, row, "Jan", text_color = text_color_, bgcolor = bg_color_, text_size = i_text_size) table.cell(table_, 2, row, "Feb", text_color = text_color_, bgcolor = bg_color_, text_size = i_text_size) table.cell(table_, 3, row, "Mar", text_color = text_color_, bgcolor = bg_color_, text_size = i_text_size) table.cell(table_, 4, row, "Apr", text_color = text_color_, bgcolor = bg_color_, text_size = i_text_size) table.cell(table_, 5, row, "May", text_color = text_color_, bgcolor = bg_color_, text_size = i_text_size) table.cell(table_, 6, row, "Jun", text_color = text_color_, bgcolor = bg_color_, text_size = i_text_size) table.cell(table_, 7, row, "Jul", text_color = text_color_, bgcolor = bg_color_, text_size = i_text_size) table.cell(table_, 8, row, "Aug", text_color = text_color_, bgcolor = bg_color_, text_size = i_text_size) table.cell(table_, 9, row, "Sep", text_color = text_color_, bgcolor = bg_color_, text_size = i_text_size) table.cell(table_, 10, row, "Oct", text_color = text_color_, bgcolor = bg_color_, text_size = i_text_size) table.cell(table_, 11, row, "Nov", text_color = text_color_, bgcolor = bg_color_, text_size = i_text_size) table.cell(table_, 12, row, "Dec", text_color = text_color_, bgcolor = bg_color_, text_size = i_text_size) for row_ = 0 to no_years_ - 1 table.cell(table_, 0, 2+row_, str.tostring(row_ + year_start_), text_color = text_color_, bgcolor = bg_color_, text_size = i_text_size) for col_ = 0 to 11 val_ = nz(matrix.get(data_, row_, col_),0.0) val_color_ = val_ > 0.0 ? color.green : val_ < 0.0 ? color.red : color.gray table.cell(table_, 1+col_, 2+row_, str.format("{0,number,###.##%}", val_), bgcolor = color.new(val_color_,80), text_color = val_color_, text_size = i_text_size) true //Aggregates row_ = no_years_ + 2 table.cell(table_, 0, row_, "AVG", text_color = text_color_, bgcolor = bg_color_, text_size = i_text_size) table.cell(table_, 0, row_+1, "SUM", text_color = text_color_, bgcolor = bg_color_, text_size = i_text_size) table.cell(table_, 0, row_+2, "+ive", text_color = text_color_, bgcolor = bg_color_, text_size = i_text_size) table.cell(table_, 0, row_+3, "WR", text_color = text_color_, bgcolor = bg_color_, text_size = i_text_size) for col_ = 0 to 11 arr_ = matrix.col(data_, col_) // val_ = array.sum(arr_) = f_array_stats(arr_) val_color_ = sum_ > 0 ? color.green : sum_ < 0 ? color.red : color.gray table.cell(table_, 1+col_, row_, str.format("{0,number,###.##%}", avg_), bgcolor = color.new(val_color_,50), text_color = val_color_, text_size = i_text_size) table.cell(table_, 1+col_, row_+1, str.format("{0,number,###.##%}", sum_), bgcolor = color.new(val_color_,50), text_color = val_color_, text_size = i_text_size) table.cell(table_, 1+col_, row_+2, str.format("{0}/{1}", count_pos_, count_), bgcolor = color.new(val_color_,50), text_color = color.new(color.white, 50), text_size = i_text_size) table.cell(table_, 1+col_, row_+3, str.format("{0,number,#.##%}", count_pos_/count_), bgcolor = color.new(val_color_,50), text_color = color.new(color.white, 50), text_size = i_text_size) true
Pine Script® indicator
by dharmeshparikh2
Events assistantThis script gives an ability to manually add events to your charts. There is no option to define events for different pairs. I trade only 2-3 pairs and it helps me a lot. It also draws vertical lines that separate trading period of your selection: daily, weekly and monthly. It is also possible to strictly define trading period. I use trading period every time during backtesting so it is easy to know when to start and when to finish. It also helps to remember that I already written down trading news during selected period.
Pine Script® indicator
by monetico
TradeQUO Herrick Payoff RSIHerrick Payoff Index RSI (HPI-RSI) with Signal Line An advanced oscillator that measures market strength not just by price, but by "smart money flow." This indicator is not a typical RSI. Instead of applying the Relative Strength Index to price alone, it calculates it on the cumulative Herrick Payoff Index (HPI) . This creates a unique oscillator that reflects the underlying sentiment and capital flow in the market. What is the Herrick Payoff Index (HPI)? The HPI is a classic sentiment indicator that combines three crucial elements to determine if money is flowing into or out of an asset: Price Change: The direction and momentum of the market. Trading Volume: The conviction behind the price movement. Open Interest (OI): The total number of open contracts (mainly in futures), which indicates if new capital is entering the market. By combining these factors, the HPI provides a more comprehensive picture of market strength than indicators based solely on price. How This Indicator Works The script follows a logical, multi-step process: It calculates the raw Herrick Payoff Index for each bar. It creates a cumulative sum of this index to generate a continuous money flow value. This cumulative value is smoothed with a short-period EMA to reduce noise. The RSI is then applied to this smoothed HPI value. An additional, configurable signal line (moving average) is added to facilitate trading signals. Interpretation and Application You can use this indicator much like a standard RSI, but with the added context of money flow: Overbought/Oversold: Values above 70 suggest an overbought condition, while values below 30 signal an oversold condition. Signal Line Crossovers: A cross of the HPI-RSI line above the signal line can be seen as a bullish signal. A cross below can be seen as a bearish signal. Divergences: Look for divergences between the indicator and the price. A bullish divergence (price makes a lower low, indicator makes a higher low) can indicate an upcoming move to the upside. A bearish divergence (price makes a higher high, indicator makes a lower high) can signal a potential move to the downside. Settings The indicator has been deliberately kept simple: HPI Smoothing Length: Smoothing length (1-5) for the cumulative HPI. RSI Length: The lookback period for the RSI calculation. Signal Line Settings: Here you can enable/disable the signal line and customize its type and length. Display Settings: Adjust the colors of the RSI and signal lines to your preference. This indicator is a tool for analysis and should always be used in combination with other methods and a solid risk management strategy. Happy trading!
Pine Script® indicator
by TradeQUO