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Dual RSI TL (AI Trend Mapper) - SigmorAlgoDual RSI TL (AI Trend Mapper) — an intelligent momentum and trendline mapping system built to give traders clarity, structure, and precision. It merges a dual-layer RSI framework (fast & slow) with automatic RSI trendlines to identify strength, exhaustion, and reversals in real time. ⚙️ Main Features: • Dual RSI system (fast & slow) with fully adjustable lengths • Automatic RSI trendline mapping (AI-driven slope detection) • Real-time crossover and confirmation alerts • Clean visual markers for entry & exit points • Compatible with EMA, SMA, and Pivot-based systems 💡 Recommended Settings: • Default: Fast = 25, Slow = 75 (1:3 ratio) — ideal balance for 15m–1D traders • Faster reaction: 12/36 or 14/42 • Slower/long-term: 28/84 or 30/90 Whether you trade scalps, intraday setups, or daily swings, Dual RSI TL adapts dynamically to price behavior — giving you a visual edge without noise. Created by SigmorAlgo — for traders who value clarity over clutter.
Penunjuk Pine Script®
oleh SigmorAlgo
Standard Deviation VolatilityThe Standard Deviation (StDev) measures the volatility or dispersion of price from its historical average. Higher values suggest greater price fluctuation and potentially a trending market. Lower values indicate lower volatility, often found during consolidation or ranging markets. 標準偏差（Standard Deviation）は、価格の過去の平均からの**ばらつき（ボラティリティ）**を測る指標です。値が高いほど価格変動が激しく、トレンド相場であることを示唆します。値が低いほど、レンジ相場または保ち合いであることを示します。
Penunjuk Pine Script®
oleh sameama
Ultimate RSI (14) TDBurbin's RSI Alerts: RSI alerts can be used ONLY when you're awaiting a chart to shift it's momentum. Example: You are waiting for a take profit signal and you'd like a push notification when this is triggered. These are NOT intended to be Buy and Sell signals. Only to get your attention. Pair with other confirmations. **There are 4 alerts. "RSI Bullish Cross" "RSI Bearish Cross" "RSI Bounce Buy" "RSI Sell". Both of the Cross alerts can be early. Can be too early. The RSI Bounce Buy and RSI Sell are when the RSI line has crossed back inside the outer bands; from Oversold or Overbought. They are a fairly reliable signal, especially when used with other TA such as support, volume, etc. Default Overbought is 80, default oversold is 20. Can be used on multiple timeframes. This is a modified version of LuxAlgo's Ultimate RSI. This is for education purposes only and personal use by Burbin. Inspired by AA, and dedicated to TD. LuxAlgo's Description: The Ultimate RSI indicator is a new oscillator based on the calculation of the Relative Strength Index that aims to put more emphasis on the trend, thus having a less noisy output. Opposite to the regular RSI, this oscillator is designed for a trend trading approach instead of a contrarian one. 🔶 USAGE While returning the same information as a regular RSI, the Ultimate RSI puts more emphasis on trends, and as such can reach overbought/oversold levels faster as well as staying longer within these areas. This can avoid the common issue of an RSI regularly crossing an overbought or oversold level while the trend makes new higher highs/lower lows. The Ultimate RSI crossing above the overbought level can be indicative of a strong uptrend (highlighted as a green area), while an Ultimate RSI crossing under the oversold level can be indicative of a strong downtrend (highlighted as a red area). The Ultimate RSI crossing the 50 midline can also indicate trends, with the oscillator being above indicating an uptrend, else a downtrend. Unlike a regular RSI, the Ultimate RSI will cross the midline level less often, thus generating fewer whipsaw signals. For even more timely indications users can observe the Ultimate RSI relative to its signal line. An Ultimate RSI above its signal line can indicate it is increasing, while the opposite would indicate it is decreasing. 🔹Smoothing Methods Users can return more reactive or smoother results depending on the selected smoothing method used for the calculation of the Ultimate RSI. Options include: Exponential Moving Average (EMA) Simple Moving Average (SMA) Wilder's Moving Average (RMA) Triangular Moving Average (TMA) These are ranked by the degree of reactivity of each method, with higher ones being more reactive (but less smooth). Users can also select the smoothing method used by the signal line. 🔶 DETAILS The RSI returns a normalized exponential average of price changes in the range (0, 100), which can be simply calculated as follows: ema(d) / ema(|d|) × 50 + 50 🔶 SETTINGS Length: Calculation period of the indicator Method: Smoothing method used for the calculation of the indicator. Source: Input source of the indicator 🔹Signal Line Smooth: Degree of smoothness of the signal line Method: Smoothing method used to calculation the signal line.
Penunjuk Pine Script®
oleh DeeeeezNuts
Ultimate RSI (2) TDBurbin's RSI Alerts: RSI alerts can be used ONLY when you're awaiting a chart to shift it's momentum. Example: You are waiting for a take profit signal and you'd like a push notification when this is triggered. These are NOT intended to be Buy and Sell signals. Only to get your attention. Pair with other confirmations. This is a modified version of LuxAlgo's Ultimate RSI. This is for education purposes only and personal use by Burbin. Inspired by AA, and dedicated to TD. LuxAlgo's Description: The Ultimate RSI indicator is a new oscillator based on the calculation of the Relative Strength Index that aims to put more emphasis on the trend, thus having a less noisy output. Opposite to the regular RSI, this oscillator is designed for a trend trading approach instead of a contrarian one. 🔶 USAGE While returning the same information as a regular RSI, the Ultimate RSI puts more emphasis on trends, and as such can reach overbought/oversold levels faster as well as staying longer within these areas. This can avoid the common issue of an RSI regularly crossing an overbought or oversold level while the trend makes new higher highs/lower lows. The Ultimate RSI crossing above the overbought level can be indicative of a strong uptrend (highlighted as a green area), while an Ultimate RSI crossing under the oversold level can be indicative of a strong downtrend (highlighted as a red area). The Ultimate RSI crossing the 50 midline can also indicate trends, with the oscillator being above indicating an uptrend, else a downtrend. Unlike a regular RSI, the Ultimate RSI will cross the midline level less often, thus generating fewer whipsaw signals. For even more timely indications users can observe the Ultimate RSI relative to its signal line. An Ultimate RSI above its signal line can indicate it is increasing, while the opposite would indicate it is decreasing. 🔹Smoothing Methods Users can return more reactive or smoother results depending on the selected smoothing method used for the calculation of the Ultimate RSI. Options include: Exponential Moving Average (EMA) Simple Moving Average (SMA) Wilder's Moving Average (RMA) Triangular Moving Average (TMA) These are ranked by the degree of reactivity of each method, with higher ones being more reactive (but less smooth). Users can also select the smoothing method used by the signal line. 🔶 DETAILS The RSI returns a normalized exponential average of price changes in the range (0, 100), which can be simply calculated as follows: ema(d) / ema(|d|) × 50 + 50 🔶 SETTINGS Length: Calculation period of the indicator Method: Smoothing method used for the calculation of the indicator. Source: Input source of the indicator 🔹Signal Line Smooth: Degree of smoothness of the signal line Method: Smoothing method used to calculation the signal line.
Penunjuk Pine Script®
oleh DeeeeezNuts
Market Regime (w/ Adaptive Thresholds)Logic Behind This Indicator This indicator identifies market regimes (trending vs. mean-reverting) using adaptive thresholds that adjust to recent market conditions. Core Components 1. Regime Score Calculation (0-100 scale) Starts at 50 (neutral) and adjusts based on two factors: A. Trend Strength Compares fast EMA (5) vs. slow EMA (10) If fast > slow by >1% → +60 points (strong uptrend) If fast < slow by >1% → -60 points (strong downtrend) B. RSI Momentum Uses 7-period RSI smoothed with 3-period EMA RSI > 70 → +20 points (overbought/trending) RSI < 30 → -20 points (oversold/mean-reverting) The score is then smoothed and clamped between 0-100. 2. Adaptive Thresholds Instead of fixed levels, thresholds adjust to recent market behavior: Looks back 100 bars to find the min/max regime score High threshold = 80% of the range (trending regime) Low threshold = 20% of the range (mean-reverting regime) This prevents false signals in different volatility environments. 3. Regime Classification Regime Score Classification Meaning Above high threshold STRONG TREND Market is trending strongly (follow momentum) Below low threshold STRONG MEAN REVERSION Market is choppy/oversold (fade moves) Between thresholds NEUTRAL No clear regime (stay out or wait) 4. Regime Persistence Filter Requires the regime to hold for a minimum number of bars (default: 1) before confirming Prevents whipsaws from brief score fluctuations What It Aims to Detect When to use trend-following strategies (green = buy breakouts, ride momentum) When to use mean-reversion strategies (red = buy dips, sell rallies) When to stay out (gray = unclear conditions, high risk of false signals) Visual Cues Green background = Strong trend (momentum strategies work) Red background = Strong mean reversion (contrarian strategies work) Table = Shows current regime, color, and score Alerts = Notifies when regime changes
Penunjuk Pine Script®
oleh Zorgs
Multiple Symbol Trend Screener [Pineify]Multiple Symbol Trend Screener Pineify – Ultimate Multi-Indicator Scanner for TradingView Empower your trading with deep market insights across multiple symbols using this feature-rich Pine Script screener. The Multiple Symbol Trend Screener Pineify enables traders to monitor and compare trends, reversals, and consolidations in real-time across the biggest equity symbols on TradingView, through a synergistic blend of popular technical indicators. Key Features Monitor up to 15 symbols and their trends simultaneously Integrates 7 professional-grade indicators: MA Distance, Aroon, Parabolic SAR (PSAR), ADX, Supertrend, Keltner Channel, and BBTrend Color-coded table display for instant visual assessment Customizable lookback periods, indicator types, and calculation methods SEO optimized for multi-symbol trend detection, screener, and advanced TradingView indicator How It Works This indicator leverages TradingView’s Pine Script v6 and request.security() to process multiple symbols across selected timeframes. Data populates a dynamic table, updating each cell based on the calculated value of every underlying indicator. MA Distance highlights deviation from moving averages; Aroon flags emerging trend strength; PSAR marks potential trend reversals; ADX assesses trend momentum; Supertrend detects bullish/bearish phases; Keltner Channel and BBTrend offer volatility and power insights. Set up your preferred symbols and timeframes Each indicator runs its calculation per symbol using its parameter group All results are displayed in a table for a comprehensive dashboard view Trading Ideas and Insights Traders can use this screener for cross-market comparison, directional bias, entry/exit filtering, and comprehensive trend evaluation. The screener is excellent for swing trading, day trading, and portfolio tracking. It enables confirmation across multiple frameworks — for example, spotting momentum with ADX before confirming direction with Supertrend and PSAR. Identify correlated movements or divergences across selected assets Spot synchronized trend changes for basket trading ideas Filter symbols by volatility, strength, or trend status for precise trade selection How Multiple Indicators Work Together The screener’s edge lies in its intelligent correlation of popular indicators. MA Distance measures the proximity to chosen moving averages, ideal for spotting overbought/oversold conditions. Aroon reveals the strength of new price trends, PSAR indicates reversal signals, and ADX quantifies the momentum of these trends. Supertrend provides a directional phase, while Keltner Channel & BBTrend analyze volatility shifts and band compressions. This amalgamation allows for a robust, multi-dimensional market snapshot, capturing details missed by single-indicator tools. By displaying all key metrics side-by-side, the screener enables holistic decision-making, revealing confluence zones and contradiction areas across multiple tickers and timeframes. Unique Aspects Original implementation combining seven independent trend and momentum indicators for each symbol Rich customization for symbols, timeframes, and all indicator parameters Intuitive color-coding for quick reading of bullish/bearish/neutral signals Comprehensive dashboard for instant actionable insights How to Use Load the indicator onto your TradingView chart Go to the script’s settings and input your preferred symbols and relevant timeframes Set your desired parameters for each indicator group: Moving Average type, Aroon length, PSAR values, ADX smoothing, etc. Observe the results in the top-right table, then use it to filter candidates and validate trade setups The screener is suitable for all timeframes and asset classes available on TradingView. Make sure your chart’s timeframe matches the one used in the scanner for optimal accuracy. Customization Choose up to 15 symbols to monitor in a single dashboard Customize lookback periods, indicator types, colors, and display settings Configure alerting options and thresholds for advanced trade automation Conclusion The Multiple Symbol Trend Screener Pineify sets a new standard for multi-asset screening on TradingView. By elegantly merging seven proven technical indicators, the screener delivers powerful trend detection, reversal analysis, and volatility monitoring — all in one dashboard. Take your trading to new heights with in-depth, customizable market surveillance.
Penunjuk Pine Script®
oleh Pineify
RSI Donchian Channel [DCAUT]█ RSI Donchian Channel 📊 ORIGINALITY & INNOVATION The RSI Donchian Channel represents an important synthesis of two complementary analytical frameworks: momentum oscillators and breakout detection systems. This indicator addresses a common limitation in traditional RSI analysis by replacing fixed overbought/oversold thresholds with adaptive zones derived from historical RSI extremes. Key Enhancement: Traditional RSI analysis relies on static threshold levels (typically 30/70), which may not adequately reflect changing market volatility regimes. This indicator adapts the reference zones dynamically based on the actual RSI behavior over the lookback period, helping traders identify meaningful momentum extremes relative to recent price action rather than arbitrary fixed levels. The implementation combines the proven momentum measurement capabilities of RSI with Donchian Channel's breakout detection methodology, creating a framework that identifies both momentum exhaustion points and potential continuation signals through the same analytical lens. 📐 MATHEMATICAL FOUNDATION Core Calculation Process: Step 1: RSI Calculation The Relative Strength Index measures momentum by comparing the magnitude of recent gains to recent losses: Calculate price changes between consecutive periods Separate positive changes (gains) from negative changes (losses) Apply selected smoothing method (RMA standard, also supports SMA, EMA, WMA) to both gain and loss series Compute Relative Strength (RS) as the ratio of smoothed gains to smoothed losses Transform RS into bounded 0-100 scale using the formula: RSI = 100 - (100 / (1 + RS)) Step 2: Donchian Channel Application The Donchian Channel identifies the highest and lowest RSI values within the specified lookback period: Upper Channel: Highest RSI value over the lookback period, represents the recent momentum peak Lower Channel: Lowest RSI value over the lookback period, represents the recent momentum trough Middle Channel (Basis): Average of upper and lower channels, serves as equilibrium reference Channel Width Dynamics: The distance between upper and lower channels reflects RSI volatility. Wide channels indicate high momentum variability, while narrow channels suggest momentum consolidation and potential breakout preparation. The indicator monitors channel width over a 100-period window to identify squeeze conditions that often precede significant momentum shifts. 📊 COMPREHENSIVE SIGNAL ANALYSIS Primary Signal Categories: Breakout Signals: Upper Breakout: RSI crosses above the upper channel, indicates momentum reaching new relative highs and potential trend continuation, particularly significant when accompanied by price confirmation Lower Breakout: RSI crosses below the lower channel, suggests momentum reaching new relative lows and potential trend exhaustion or reversal setup Breakout strength is enhanced when the channel is narrow prior to the breakout, indicating a transition from consolidation to directional movement Mean Reversion Signals: Upper Touch Without Breakout: RSI reaches the upper channel but fails to break through, may indicate momentum exhaustion and potential reversal opportunity Lower Touch Without Breakout: RSI reaches the lower channel without breakdown, suggests potential bounce as momentum reaches oversold extremes Return to Basis: RSI moving back toward the middle channel after touching extremes signals momentum normalization Trend Strength Assessment: Sustained Upper Channel Riding: RSI consistently remains near or above the upper channel during strong uptrends, indicates persistent bullish momentum Sustained Lower Channel Riding: RSI stays near or below the lower channel during strong downtrends, reflects persistent bearish pressure Basis Line Position: RSI position relative to the middle channel helps identify the prevailing momentum bias Channel Compression Patterns: Squeeze Detection: Channel width narrowing to 100-period lows indicates momentum consolidation, often precedes significant directional moves Expansion Phase: Channel widening after a squeeze confirms the initiation of a new momentum regime Persistent Narrow Channels: Extended periods of tight channels suggest market indecision and accumulation/distribution phases 🎯 STRATEGIC APPLICATIONS Trend Continuation Strategy: This approach focuses on identifying and trading momentum breakouts that confirm established trends: Identify the prevailing price trend using higher timeframe analysis or trend-following indicators Wait for RSI to break above the upper channel in uptrends (or below the lower channel in downtrends) Enter positions in the direction of the breakout when price action confirms the momentum shift Place protective stops below the recent swing low (long positions) or above swing high (short positions) Target profit levels based on prior swing extremes or use trailing stops to capture extended moves Exit when RSI crosses back through the basis line in the opposite direction Mean Reversion Strategy: This method capitalizes on momentum extremes and subsequent corrections toward equilibrium: Monitor for RSI reaching the upper or lower channel boundaries Look for rejection signals (price reversal patterns, volume divergence) when RSI touches the channels Enter counter-trend positions when RSI begins moving back toward the basis line Use the basis line as the initial profit target for mean reversion trades Implement tight stops beyond the channel extremes to limit risk on failed reversals Scale out of positions as RSI approaches the basis line and closes the position when RSI crosses the basis Breakout Preparation Strategy: This approach positions traders ahead of potential volatility expansion from consolidation phases: Identify squeeze conditions when channel width reaches 100-period lows Monitor price action for consolidation patterns (triangles, rectangles, flags) during the squeeze Prepare conditional orders for breakouts in both directions from the consolidation Enter positions when RSI breaks out of the narrow channel with expanding width Use the channel width expansion as a confirmation signal for the breakout's validity Manage risk with stops just inside the opposite channel boundary Multi-Timeframe Confluence Strategy: Combining RSI Donchian Channel analysis across multiple timeframes can improve signal reliability: Identify the primary trend direction using a higher timeframe RSI Donchian Channel (e.g., daily or weekly) Use a lower timeframe (e.g., 4-hour or hourly) to time precise entry points Enter long positions when both timeframes show RSI above their respective basis lines Enter short positions when both timeframes show RSI below their respective basis lines Avoid trades when timeframes provide conflicting signals (e.g., higher timeframe below basis, lower timeframe above) Exit when the higher timeframe RSI crosses its basis line in the opposite direction Risk Management Guidelines: Effective risk management is essential for all RSI Donchian Channel strategies: Position Sizing: Calculate position sizes based on the distance between entry point and stop loss, limiting risk to 1-2% of capital per trade Stop Loss Placement: For breakout trades, place stops just inside the opposite channel boundary; for mean reversion trades, use stops beyond the channel extremes Profit Targets: Use the basis line as a minimum target for mean reversion trades; for trend trades, target prior swing extremes or use trailing stops Channel Width Context: Increase position sizes during narrow channels (lower volatility) and reduce sizes during wide channels (higher volatility) Correlation Awareness: Monitor correlations between traded instruments to avoid over-concentration in similar setups 📋 DETAILED PARAMETER CONFIGURATION RSI Source: Defines the price data series used for RSI calculation: Close (Default): Standard choice providing end-of-period momentum assessment, suitable for most trading styles and timeframes High-Low Average (HL2): Reduces the impact of closing auction dynamics, useful for markets with significant end-of-day volatility High-Low-Close Average (HLC3): Provides a more balanced view incorporating the entire period's range Open-High-Low-Close Average (OHLC4): Offers the most comprehensive price representation, helpful for identifying overall period sentiment Strategy Consideration: Use Close for end-of-period signals, HL2 or HLC3 for intraday volatility reduction, OHLC4 for capturing full period dynamics RSI Length: Controls the number of periods used for RSI calculation: Short Periods (5-9): Highly responsive to recent price changes, produces more frequent signals with increased false signal risk, suitable for short-term trading and volatile markets Standard Period (14): Widely accepted default balancing responsiveness with stability, appropriate for swing trading and intermediate-term analysis Long Periods (21-28): Produces smoother RSI with fewer signals but more reliable trend identification, better for position trading and reducing noise in choppy markets Optimization Approach: Test different lengths against historical data for your specific market and timeframe, consider using longer periods in ranging markets and shorter periods in trending markets RSI MA Type: Determines the smoothing method applied to price changes in RSI calculation: RMA (Relative Moving Average - Default): Wilder's original smoothing method providing stable momentum measurement with gradual response to changes, maintains consistency with classical RSI interpretation SMA (Simple Moving Average): Treats all periods equally, responds more quickly to changes than RMA but may produce more whipsaws in volatile conditions EMA (Exponential Moving Average): Weights recent periods more heavily, increases responsiveness at the cost of potential noise, suitable for traders prioritizing early signal generation WMA (Weighted Moving Average): Applies linear weighting favoring recent data, offers a middle ground between SMA and EMA responsiveness Selection Guidance: Maintain RMA for consistency with traditional RSI analysis, use EMA or WMA for more responsive signals in fast-moving markets, apply SMA for maximum simplicity and transparency DC Length: Specifies the lookback period for Donchian Channel calculation on RSI values: Short Periods (10-14): Creates tight channels that adapt quickly to changing momentum conditions, generates more frequent trading signals but increases sensitivity to short-term RSI fluctuations Standard Period (20): Balances channel responsiveness with stability, aligns with traditional Bollinger Bands and moving average periods, suitable for most trading styles Long Periods (30-50): Produces wider, more stable channels that better represent sustained momentum extremes, reduces signal frequency while improving reliability, appropriate for position traders and higher timeframes Calibration Strategy: Match DC length to your trading timeframe (shorter for day trading, longer for swing trading), test channel width behavior during different market regimes, consider using adaptive periods that adjust to volatility conditions Market Adaptation: Use shorter DC lengths in trending markets to capture momentum shifts earlier, apply longer periods in ranging markets to filter noise and focus on significant extremes Parameter Combination Recommendations: Scalping/Day Trading: RSI Length 5-9, DC Length 10-14, EMA or WMA smoothing for maximum responsiveness Swing Trading: RSI Length 14, DC Length 20, RMA smoothing for balanced analysis (default configuration) Position Trading: RSI Length 21-28, DC Length 30-50, RMA or SMA smoothing for stable signals High Volatility Markets: Longer RSI periods (21+) with standard DC length (20) to reduce noise Low Volatility Markets: Standard RSI length (14) with shorter DC length (10-14) to capture subtle momentum shifts 📈 PERFORMANCE ANALYSIS & COMPETITIVE ADVANTAGES Adaptive Threshold Mechanism: Unlike traditional RSI analysis with fixed 30/70 thresholds, this indicator's Donchian Channel approach provides several improvements: Context-Aware Extremes: Overbought/oversold levels adjust automatically based on recent momentum behavior rather than arbitrary fixed values Volatility Adaptation: In low volatility periods, channels narrow to reflect tighter momentum ranges; in high volatility, channels widen appropriately Market Regime Recognition: The indicator implicitly adapts to different market conditions without manual threshold adjustments False Signal Reduction: Adaptive channels help reduce premature reversal signals that often occur with fixed thresholds during strong trends Signal Quality Characteristics: The indicator's dual-purpose design provides distinct advantages for different trading objectives: Breakout Trading: Channel boundaries offer clear, objective breakout levels that update dynamically, eliminating the ambiguity of when momentum becomes "too high" or "too low" Mean Reversion: The basis line provides a natural profit target for reversion trades, representing the midpoint of recent momentum extremes Trend Strength: Persistent channel boundary riding offers an objective measure of trend strength without additional indicators Consolidation Detection: Channel width analysis provides early warning of potential volatility expansion from compression phases Comparative Analysis: When compared to traditional RSI implementations and other momentum frameworks: vs. Fixed Threshold RSI: Provides market-adaptive reference levels rather than static values, helping to reduce false signals during trending markets where RSI can remain "overbought" or "oversold" for extended periods vs. RSI Bollinger Bands: Offers clearer breakout signals and more intuitive extreme identification through actual high/low boundaries rather than statistical standard deviations vs. Stochastic Oscillator: Maintains RSI's momentum measurement advantages (unbounded calculation avoiding scale compression) while adding the breakout detection capabilities of Donchian Channels vs. Standard Donchian Channels: Applies breakout methodology to momentum space rather than price, providing earlier signals of potential trend changes before price breakouts occur Performance Characteristics: The indicator exhibits specific behavioral patterns across different market conditions: Trending Markets: Excels at identifying momentum continuation through channel breakouts, RSI tends to ride one channel boundary during strong trends, providing trend confirmation Ranging Markets: Channel width narrows during consolidation, offering early preparation signals for potential breakout trading opportunities High Volatility: Channels widen to reflect increased momentum variability, automatically adjusting signal sensitivity to match market conditions Low Volatility: Channels contract, making the indicator more sensitive to subtle momentum shifts that may be significant in calm market environments Transition Periods: Channel squeezes often precede major trend changes, offering advance warning of potential regime shifts Limitations and Considerations: Users should be aware of certain operational characteristics: Lookback Dependency: Channel boundaries depend entirely on the lookback period, meaning the indicator has no predictive element beyond identifying current momentum relative to recent history Lag Characteristics: As with all moving average-based indicators, RSI calculation introduces lag, and channel boundaries update only as new extremes occur within the lookback window Range-Bound Sensitivity: In extremely tight ranges, channels may become very narrow, potentially generating excessive signals from minor momentum fluctuations Trending Persistence: During very strong trends, RSI may remain at channel extremes for extended periods, requiring patience for mean reversion setups or commitment to trend-following approaches No Absolute Levels: Unlike traditional RSI, this indicator provides no fixed reference points (like 50), making it less suitable for strategies that depend on absolute momentum readings USAGE NOTES This indicator is designed for technical analysis and educational purposes to help traders understand momentum dynamics and identify potential trading opportunities. The RSI Donchian Channel has limitations and should not be used as the sole basis for trading decisions. Important considerations: Performance varies significantly across different market conditions, timeframes, and instruments Historical signal patterns do not guarantee future results, as market behavior continuously evolves Effective use requires understanding of both RSI momentum principles and Donchian Channel breakout concepts Risk management practices (stop losses, position sizing, diversification) are essential for any trading application Consider combining with additional analytical tools such as volume analysis, price action patterns, or trend indicators for confirmation Backtest thoroughly on your specific instruments and timeframes before live trading implementation Be aware that optimization on historical data may lead to curve-fitting and poor forward performance The indicator performs best when used as part of a comprehensive trading methodology that incorporates multiple forms of market analysis, sound risk management, and realistic expectations about win rates and drawdowns.
Penunjuk Pine Script®
oleh DCAUT
Stochastic Arrows Crossover with Alerts [TED]This indicator highlights key Stochastic %K and %D crossovers, helping traders identify potential buy and sell signals with visual triangle arrows and custom alerts. It uses the Stochastic Oscillator, which is a momentum indicator that compares the closing price to the price range over a given period. Key Features: Visual Arrows: The indicator plots green triangle-up arrows for bullish crossovers and red triangle-down arrows for bearish crossovers on the chart. Customizable Parameters: You can adjust the period for %K, %D, and the smoothing factor to fit your trading strategy. Overbought/Oversold Zones: The background color fills between the 80 (Overbought) and 20 (Oversold) levels, helping you visualize potential reversal areas. Alerts: Set up dynamic alerts based on the crossover events, including: Bullish and Bearish Crossovers Crossover Events from the Previous Bar How to Use: Bullish Signal: When the %K line crosses above the %D line, it signals a potential buying opportunity. This is visually represented with a green triangle-up arrow on the chart. Bearish Signal: When the %K line crosses below the %D line, it signals a potential selling opportunity, indicated by a red triangle-down arrow on the chart. Overbought/Oversold Zones: The background color fill helps identify overbought or oversold market conditions, which may indicate a potential reversal. Custom Alerts: You can set alerts for: Bullish Crossover: When the %K line crosses above the %D line. Bearish Crossover: When the %K line crosses below the %D line. Previous Bar Crossovers: Alerts for crossovers from one bar ago (helpful for backtesting). Instructions: Add the Indicator: Apply this Stochastic Arrows Crossover indicator to your chart from the public library. Customize Settings: Adjust the input parameters like K period, D period, and Smoothing to match your preferred settings. Enable Alerts: Once added to your chart, you can set up alerts from the Alert Panel on TradingView. Choose from the available alert conditions (Bullish Crossover, Bearish Crossover, or Crossover from the Previous Bar). Set your desired timeframe and alert message to receive notifications for the crossovers. Monitor the Chart: Keep an eye on the arrows and background color fill to interpret potential trade setups based on the Stochastic Oscillator's behavior.
Penunjuk Pine Script®
oleh jasperdiaz45
MILLION MEN - Peaks & Dips MeterWhat it is The MILLION MEN — Peaks & Dips Meter is a dynamic momentum visualization tool designed to identify extreme strength and exhaustion zones. It uses two selectable engines: RSI Meter (ZS Core) for classic strength analysis. OB/OS Multi-Length (ZS Quick Core) for adaptive readings that reflect multi-period sentiment shifts. How it works The script computes normalized momentum values (0–100) from price dynamics, builds a smooth gradient representation, and displays it as a fixed right-bottom table. The meter color scales between fuchsia and green, with optional candle coloring and percentage labels. It can also highlight overbought (peaks) and oversold (dips) moments directly on candles with adjustable ATR offsets and label styles. How to use Values near 90–100% → potential short-term exhaustion (watch for reversals). Values near 0–10% → potential accumulation zones (possible bounces). Use together with structure, volume, or trend filters for confirmation. Originality Unlike standard RSI tools, this script merges multi-length OB/OS detection with a real-time visual meter, optimized for scalpers and visual traders. It does not repaint and maintains a lightweight structure for fast responsiveness. Limitations This indicator is for analysis purposes only and should not be considered financial advice. Past readings do not guarantee future performance.
Penunjuk Pine Script®
oleh MILLION_MEN
Stochastic Enhanced [DCAUT]█ Stochastic Enhanced 📊 ORIGINALITY & INNOVATION The Stochastic Enhanced indicator builds upon George Lane's classic momentum oscillator (developed in the late 1950s) by providing comprehensive smoothing algorithm flexibility. While traditional implementations limit users to Simple Moving Average (SMA) smoothing, this enhanced version offers 21 advanced smoothing algorithms, allowing traders to optimize the indicator's characteristics for different market conditions and trading styles. Key Improvements: Extended from single SMA smoothing to 21 professional-grade algorithms including adaptive filters (KAMA, FRAMA), zero-lag methods (ZLEMA, T3), and advanced digital filters (Kalman, Laguerre) Maintains backward compatibility with traditional Stochastic calculations through SMA default setting Unified smoothing algorithm applies to both %K and %D lines for consistent signal processing characteristics Enhanced visual feedback with clear color distinction and background fill highlighting for intuitive signal recognition Comprehensive alert system covering crossovers and zone entries for systematic trade management Differentiation from Traditional Stochastic: Traditional Stochastic indicators use fixed SMA smoothing, which introduces consistent lag regardless of market volatility. This enhanced version addresses the limitation by offering adaptive algorithms that adjust to market conditions (KAMA, FRAMA), reduce lag without sacrificing smoothness (ZLEMA, T3, HMA), or provide superior noise filtering (Kalman Filter, Laguerre filters). The flexibility helps traders balance responsiveness and stability according to their specific needs. 📐 MATHEMATICAL FOUNDATION Core Stochastic Calculation: The Stochastic Oscillator measures the position of the current close relative to the high-low range over a specified period: Step 1: Raw %K Calculation %K_raw = 100 × (Close - Lowest Low) / (Highest High - Lowest Low) Where: Close = Current closing price Lowest Low = Lowest low over the %K Length period Highest High = Highest high over the %K Length period Result ranges from 0 (close at period low) to 100 (close at period high) Step 2: Smoothed %K Calculation %K = MA(%K_raw, K Smoothing Period, MA Type) Where: MA = Selected moving average algorithm (SMA, EMA, etc.) K Smoothing = 1 for Fast Stochastic, 3+ for Slow Stochastic Traditional Fast Stochastic uses %K_raw directly without smoothing Step 3: Signal Line %D Calculation %D = MA(%K, D Smoothing Period, MA Type) Where: %D acts as a signal line and moving average of %K D Smoothing typically set to 3 periods in traditional implementations Both %K and %D use the same MA algorithm for consistent behavior Available Smoothing Algorithms (21 Options): Standard Moving Averages: SMA (Simple): Equal-weighted average, traditional default, consistent lag characteristics EMA (Exponential): Recent price emphasis, faster response to changes, exponential decay weighting RMA (Rolling/Wilder's): Smoothed average used in RSI, less reactive than EMA WMA (Weighted): Linear weighting favoring recent data, moderate responsiveness VWMA (Volume-Weighted): Incorporates volume data, reflects market participation intensity Advanced Moving Averages: HMA (Hull): Reduced lag with smoothness, uses weighted moving averages and square root period ALMA (Arnaud Legoux): Gaussian distribution weighting, minimal lag with good noise reduction LSMA (Least Squares): Linear regression based, fits trend line to data points DEMA (Double Exponential): Reduced lag compared to EMA, uses double smoothing technique TEMA (Triple Exponential): Further lag reduction, triple smoothing with lag compensation ZLEMA (Zero-Lag Exponential): Lag elimination attempt using error correction, very responsive TMA (Triangular): Double-smoothed SMA, very smooth but slower response Adaptive & Intelligent Filters: T3 (Tilson T3): Six-pass exponential smoothing with volume factor adjustment, excellent smoothness FRAMA (Fractal Adaptive): Adapts to market fractal dimension, faster in trends, slower in ranges KAMA (Kaufman Adaptive): Efficiency ratio based adaptation, responds to volatility changes McGinley Dynamic: Self-adjusting mechanism following price more accurately, reduced whipsaws Kalman Filter: Optimal estimation algorithm from aerospace engineering, dynamic noise filtering Advanced Digital Filters: Ultimate Smoother: Advanced digital filter design, superior noise rejection with minimal lag Laguerre Filter: Time-domain filter with N-order implementation, adjustable lag characteristics Laguerre Binomial Filter: 6-pole Laguerre filter, extremely smooth output for long-term analysis Super Smoother: Butterworth filter implementation, removes high-frequency noise effectively 📊 COMPREHENSIVE SIGNAL ANALYSIS Absolute Level Interpretation (%K Line): %K Above 80: Overbought condition, price near period high, potential reversal or pullback zone, caution for new long entries %K in 70-80 Range: Strong upward momentum, bullish trend confirmation, uptrend likely continuing %K in 50-70 Range: Moderate bullish momentum, neutral to positive outlook, consolidation or mild uptrend %K in 30-50 Range: Moderate bearish momentum, neutral to negative outlook, consolidation or mild downtrend %K in 20-30 Range: Strong downward momentum, bearish trend confirmation, downtrend likely continuing %K Below 20: Oversold condition, price near period low, potential bounce or reversal zone, caution for new short entries Crossover Signal Analysis: %K Crosses Above %D (Bullish Cross): Momentum shifting bullish, faster line overtakes slower signal, consider long entry especially in oversold zone, strongest when occurring below 20 level %K Crosses Below %D (Bearish Cross): Momentum shifting bearish, faster line falls below slower signal, consider short entry especially in overbought zone, strongest when occurring above 80 level Crossover in Midrange (40-60): Less reliable signals, often in choppy sideways markets, require additional confirmation from trend or volume analysis Multiple Failed Crosses: Indicates ranging market or choppy conditions, reduce position sizes or avoid trading until clear directional move Advanced Divergence Patterns (%K Line vs Price): Bullish Divergence: Price makes lower low while %K makes higher low, indicates weakening bearish momentum, potential trend reversal upward, more reliable when %K in oversold zone Bearish Divergence: Price makes higher high while %K makes lower high, indicates weakening bullish momentum, potential trend reversal downward, more reliable when %K in overbought zone Hidden Bullish Divergence: Price makes higher low while %K makes lower low, indicates trend continuation in uptrend, bullish trend strength confirmation Hidden Bearish Divergence: Price makes lower high while %K makes higher high, indicates trend continuation in downtrend, bearish trend strength confirmation Momentum Strength Analysis (%K Line Slope): Steep %K Slope: Rapid momentum change, strong directional conviction, potential for extended moves but also increased reversal risk Gradual %K Slope: Steady momentum development, sustainable trends more likely, lower probability of sharp reversals Flat or Horizontal %K: Momentum stalling, potential reversal or consolidation ahead, wait for directional break before committing %K Oscillation Within Range: Indicates ranging market, sideways price action, better suited for range-trading strategies than trend following 🎯 STRATEGIC APPLICATIONS Mean Reversion Strategy (Range-Bound Markets): Identify ranging market conditions using price action or Bollinger Bands Wait for Stochastic to reach extreme zones (above 80 for overbought, below 20 for oversold) Enter counter-trend position when %K crosses %D in extreme zone (sell on bearish cross above 80, buy on bullish cross below 20) Set profit targets near opposite extreme or midline (50 level) Use tight stop-loss above recent swing high/low to protect against breakout scenarios Exit when Stochastic reaches opposite extreme or %K crosses %D in opposite direction Trend Following with Momentum Confirmation: Identify primary trend direction using higher timeframe analysis or moving averages Wait for Stochastic pullback to oversold zone (<20) in uptrend or overbought zone (>80) in downtrend Enter in trend direction when %K crosses %D confirming momentum shift (bullish cross in uptrend, bearish cross in downtrend) Use wider stops to accommodate normal trend volatility Add to position on subsequent pullbacks showing similar Stochastic pattern Exit when Stochastic shows opposite extreme with failed cross or bearish/bullish divergence Divergence-Based Reversal Strategy: Scan for divergence between price and Stochastic at swing highs/lows Confirm divergence with at least two price pivots showing divergent Stochastic readings Wait for %K to cross %D in direction of anticipated reversal as entry trigger Enter position in divergence direction with stop beyond recent swing extreme Target profit at key support/resistance levels or Fibonacci retracements Scale out as Stochastic reaches opposite extreme zone Multi-Timeframe Momentum Alignment: Analyze Stochastic on higher timeframe (4H or Daily) for primary trend bias Switch to lower timeframe (1H or 15M) for precise entry timing Only take trades where lower timeframe Stochastic signal aligns with higher timeframe momentum direction Higher timeframe Stochastic in bullish zone (>50) = only take long entries on lower timeframe Higher timeframe Stochastic in bearish zone (<50) = only take short entries on lower timeframe Exit when lower timeframe shows counter-signal or higher timeframe momentum reverses Zone Transition Strategy: Monitor Stochastic for transitions between zones (oversold to neutral, neutral to overbought, etc.) Enter long when Stochastic crosses above 20 (exiting oversold), signaling momentum shift from bearish to neutral/bullish Enter short when Stochastic crosses below 80 (exiting overbought), signaling momentum shift from bullish to neutral/bearish Use zone midpoint (50) as dynamic support/resistance for position management Trail stops as Stochastic advances through favorable zones Exit when Stochastic fails to maintain momentum and reverses back into prior zone 📋 DETAILED PARAMETER CONFIGURATION %K Length (Default: 14): Lower Values (5-9): Highly sensitive to price changes, generates more frequent signals, increased false signals in choppy markets, suitable for very short-term trading and scalping Standard Values (10-14): Balanced sensitivity and reliability, traditional default (14) widely used,适合 swing trading and intraday strategies Higher Values (15-21): Reduced sensitivity, smoother oscillations, fewer but potentially more reliable signals, better for position trading and lower timeframe noise reduction Very High Values (21+): Slow response, long-term momentum measurement, fewer trading signals, suitable for weekly or monthly analysis %K Smoothing (Default: 3): Value 1: Fast Stochastic, uses raw %K calculation without additional smoothing, most responsive to price changes, generates earliest signals with higher noise Value 3: Slow Stochastic (default), traditional smoothing level, reduces false signals while maintaining good responsiveness, widely accepted standard Values 5-7: Very slow response, extremely smooth oscillations, significantly reduced whipsaws but delayed entry/exit timing Recommendation: Default value 3 suits most trading scenarios, active short-term traders may use 1, conservative long-term positions use 5+ %D Smoothing (Default: 3): Lower Values (1-2): Signal line closely follows %K, frequent crossover signals, useful for active trading but requires strict filtering Standard Value (3): Traditional setting providing balanced signal line behavior, optimal for most trading applications Higher Values (4-7): Smoother signal line, fewer crossover signals, reduced whipsaws but slower confirmation, better for trend trading Very High Values (8+): Signal line becomes slow-moving reference, crossovers rare and highly significant, suitable for long-term position changes only Smoothing Type Algorithm Selection: For Trending Markets: ZLEMA, DEMA, TEMA: Reduced lag for faster trend entry, quick response to momentum shifts, suitable for strong directional moves HMA, ALMA: Good balance of smoothness and responsiveness, effective for clean trend following without excessive noise EMA: Classic choice for trending markets, faster than SMA while maintaining reasonable stability For Ranging/Choppy Markets: Kalman Filter, Super Smoother: Superior noise filtering, reduces false signals in sideways action, helps identify genuine reversal points Laguerre Filters: Smooth oscillations with adjustable lag, excellent for mean reversion strategies in ranges T3, TMA: Very smooth output, filters out market noise effectively, clearer extreme zone identification For Adaptive Market Conditions: KAMA: Automatically adjusts to market efficiency, fast in trends and slow in congestion, reduces whipsaws during transitions FRAMA: Adapts to fractal market structure, responsive during directional moves, conservative during uncertainty McGinley Dynamic: Self-adjusting smoothing, follows price naturally, minimizes lag in trending markets while filtering noise in ranges For Conservative Long-Term Analysis: SMA: Traditional choice, predictable behavior, widely understood characteristics RMA (Wilder's): Smooth oscillations, reduced sensitivity to outliers, consistent behavior across market conditions Laguerre Binomial Filter: Extremely smooth output, ideal for weekly/monthly timeframe analysis, eliminates short-term noise completely Source Selection: Close (Default): Standard choice using closing prices, most common and widely tested HLC3 or OHLC4: Incorporates more price information, reduces impact of sudden spikes or gaps, smoother oscillator behavior HL2: Midpoint of high-low range, emphasizes intrabar volatility, useful for markets with wide intraday ranges Custom Source: Can use other indicators as input (e.g., Heikin Ashi close, smoothed price), creates derivative momentum indicators 📈 PERFORMANCE ANALYSIS & COMPETITIVE ADVANTAGES Responsiveness Characteristics: Traditional SMA-Based Stochastic: Fixed lag regardless of market conditions, consistent delay of approximately (K Smoothing + D Smoothing) / 2 periods Equal treatment of trending and ranging markets, no adaptation to volatility changes Predictable behavior but suboptimal in varying market regimes Enhanced Version with Adaptive Algorithms: KAMA and FRAMA reduce lag by up to 40-60% in strong trends compared to SMA while maintaining similar smoothness in ranges ZLEMA and T3 provide near-zero lag characteristics for early entry signals with acceptable noise levels Kalman Filter and Super Smoother offer superior noise rejection, reducing false signals in choppy conditions by estimations of 30-50% compared to SMA Performance improvements vary by algorithm selection and market conditions Signal Quality Improvements: Adaptive algorithms help reduce whipsaw trades in ranging markets by adjusting sensitivity dynamically Advanced filters (Kalman, Laguerre, Super Smoother) provide clearer extreme zone readings for mean reversion strategies Zero-lag methods (ZLEMA, DEMA, TEMA) generate earlier crossover signals in trending markets for improved entry timing Smoother algorithms (T3, Laguerre Binomial) reduce false extreme zone touches for more reliable overbought/oversold signals Comparison with Standard Implementations: Versus Basic Stochastic: Enhanced version offers 21 smoothing options versus single SMA, allowing optimization for specific market characteristics and trading styles Versus RSI: Stochastic provides range-bound measurement (0-100) with clear extreme zones, RSI measures momentum speed, Stochastic offers clearer visual overbought/oversold identification Versus MACD: Stochastic bounded oscillator suitable for mean reversion, MACD unbounded indicator better for trend strength, Stochastic excels in range-bound and oscillating markets Versus CCI: Stochastic has fixed bounds (0-100) for consistent interpretation, CCI unbounded with variable extremes, Stochastic provides more standardized extreme readings across different instruments Flexibility Advantages: Single indicator adaptable to multiple strategies through algorithm selection rather than requiring different indicator variants Ability to optimize smoothing characteristics for specific instruments (e.g., smoother for crypto volatility, faster for forex trends) Multi-timeframe analysis with consistent algorithm across timeframes for coherent momentum picture Backtesting capability with algorithm as optimization parameter for strategy development Limitations and Considerations: Increased complexity from multiple algorithm choices may lead to over-optimization if parameters are curve-fitted to historical data Adaptive algorithms (KAMA, FRAMA) have adjustment periods during market regime changes where signals may be less reliable Zero-lag algorithms sacrifice some smoothness for responsiveness, potentially increasing noise sensitivity in very choppy conditions Performance characteristics vary significantly across algorithms, requiring understanding and testing before live implementation Like all oscillators, Stochastic can remain in extreme zones for extended periods during strong trends, generating premature reversal signals USAGE NOTES This indicator is designed for technical analysis and educational purposes to provide traders with enhanced flexibility in momentum analysis. The Stochastic Oscillator has limitations and should not be used as the sole basis for trading decisions. Important Considerations: Algorithm performance varies with market conditions - no single smoothing method is optimal for all scenarios Extreme zone signals (overbought/oversold) indicate potential reversal areas but not guaranteed turning points, especially in strong trends Crossover signals may generate false entries during sideways choppy markets regardless of smoothing algorithm Divergence patterns require confirmation from price action or additional indicators before trading Past indicator characteristics and backtested results do not guarantee future performance Always combine Stochastic analysis with proper risk management, position sizing, and multi-indicator confirmation Test selected algorithm on historical data of specific instrument and timeframe before live trading Market regime changes may require algorithm adjustment for optimal performance The enhanced smoothing options are intended to provide tools for optimizing the indicator's behavior to match individual trading styles and market characteristics, not to create a perfect predictive tool. Responsible usage includes understanding the mathematical properties of selected algorithms and their appropriate application contexts.
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