Black Friday최대 80% 싸게

오실레이터

Chanpreet RSI(3) Extreme Rays (4H, Adjustable Style)Chanpreet RSI(3) Extreme Rays (4H) This indicator applies a short-length RSI (3) on the 4-hour timeframe and highlights momentum extremes directly on the chart. 🔎 What it does Detects when RSI(3) moves into overbought (>80) or oversold (<20) territory. Groups consecutive candles inside these zones into one “event” instead of marking each bar individually. For each event: • In overbought → records the highest high of the stretch and marks it with a horizontal ray. • In oversold → records the lowest low of the stretch and marks it with a horizontal ray. Keeps only the most recent N rays (default 5, adjustable). ⚙️ Inputs Max Rays to Keep → how many unique events are kept visible. Ray Thickness → adjust line thickness. Overbought Ray Color → default red. Oversold Ray Color → default green. 📈 How to use Apply on any chart; RSI(3) values are always calculated from 4H data (via request.security). Use rays as reference levels that highlight recent momentum extremes or exhaustion zones. This is not a buy/sell signal by itself — combine with your own analysis, confirmation tools, and risk management. Best Recommended time frame is 5 mins, 10 mins & 15 mins for intraday trading. 🧩 Unique features Groups multiple bars into a single clean ray, reducing clutter. Uses 4H RSI(3) regardless of the chart’s active timeframe. Fully customizable appearance (colors, thickness, max events). ⚠️ Disclaimer This script is provided for educational and informational purposes only. It does not constitute financial advice or guarantee performance. Always test thoroughly and use proper risk management before trading live.
Pine Script® 인디케이터
Sensible_Trader의
1
Machine Learning Gaussian Mixture Model | AlphaNattMachine Learning Gaussian Mixture Model | AlphaNatt A revolutionary oscillator that uses Gaussian Mixture Models (GMM) with unsupervised machine learning to identify market regimes and automatically adapt momentum calculations - bringing statistical pattern recognition techniques to trading. "Markets don't follow a single distribution - they're a mixture of different regimes. This oscillator identifies which regime we're in and adapts accordingly." ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 🤖 THE MACHINE LEARNING Gaussian Mixture Models (GMM): Unlike K-means clustering which assigns hard boundaries, GMM uses probabilistic clustering : Models data as coming from multiple Gaussian distributions Each market regime is a different Gaussian component Provides probability of belonging to each regime More sophisticated than simple clustering Expectation-Maximization Algorithm: The indicator continuously learns and adapts using the E-M algorithm: E-step: Calculate probability of current market belonging to each regime M-step: Update regime parameters based on new data Continuous learning without repainting Adapts to changing market conditions ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 🎯 THREE MARKET REGIMES The GMM identifies three distinct market states: Regime 1 - Low Volatility: Quiet, ranging markets Uses RSI-based momentum calculation Reduces false signals in choppy conditions Background: Pink tint Regime 2 - Normal Market: Standard trending conditions Uses Rate of Change momentum Balanced sensitivity Background: Gray tint Regime 3 - High Volatility: Strong trends or volatility events Uses Z-score based momentum Captures extreme moves Background: Cyan tint ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 💡 KEY INNOVATIONS 1. Probabilistic Regime Detection: Instead of binary regime assignment, provides probabilities: 30% Regime 1, 60% Regime 2, 10% Regime 3 Smooth transitions between regimes No sudden indicator jumps 2. Weighted Momentum Calculation: Combines three different momentum formulas Weights based on regime probabilities Automatically adapts to market conditions 3. Confidence Indicator: Shows how certain the model is (white line) High confidence = strong regime identification Low confidence = transitional market state Line transparency changes with confidence ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ ⚙️ PARAMETER OPTIMIZATION Training Period (50-500): 50-100: Quick adaptation to recent conditions 100: Balanced (default) 200-500: Stable regime identification Number of Components (2-5): 2: Simple bull/bear regimes 3: Low/Normal/High volatility (default) 4-5: More granular regime detection Learning Rate (0.1-1.0): 0.1-0.3: Slow, stable learning 0.3: Balanced (default) 0.5-1.0: Fast adaptation ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 📊 TRADING STRATEGIES Visual Signals: Cyan gradient: Bullish momentum Magenta gradient: Bearish momentum Background color: Current regime Confidence line: Model certainty 1. Regime-Based Trading: Regime 1 (pink): Expect mean reversion Regime 2 (gray): Standard trend following Regime 3 (cyan): Strong momentum trades 2. Confidence-Filtered Signals: Only trade when confidence > 70% High confidence = clearer market state Avoid transitions (low confidence) 3. Adaptive Position Sizing: Regime 1: Smaller positions (choppy) Regime 2: Normal positions Regime 3: Larger positions (trending) ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 🚀 ADVANTAGES OVER OTHER ML INDICATORS vs K-Means Clustering: Soft clustering (probabilities) vs hard boundaries Captures uncertainty and transitions More mathematically robust vs KNN (K-Nearest Neighbors): Unsupervised learning (no historical labels needed) Continuous adaptation Lower computational complexity vs Neural Networks: Interpretable (know what each regime means) No overfitting issues Works with limited data ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 📈 PERFORMANCE CHARACTERISTICS Best Market Conditions: Markets with clear regime shifts Volatile to trending transitions Multi-timeframe analysis Cryptocurrency markets (high regime variation) Key Strengths: Automatically adapts to market changes No manual parameter adjustment needed Smooth transitions between regimes Probabilistic confidence measure ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 🔬 TECHNICAL BACKGROUND Gaussian Mixture Models are used extensively in: Speech recognition (Google Assistant) Computer vision (facial recognition) Astronomy (galaxy classification) Genomics (gene expression analysis) Finance (risk modeling at investment banks) The E-M algorithm was developed at Stanford in 1977 and is one of the most important algorithms in unsupervised machine learning. ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 💡 PRO TIPS Watch regime transitions: Best opportunities often occur when regimes change Combine with volume: High volume + regime change = strong signal Use confidence filter: Avoid low confidence periods Multi-timeframe: Compare regimes across timeframes Adjust position size: Scale based on identified regime ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ ⚠️ IMPORTANT NOTES Machine learning adapts but doesn't predict the future Best used with other confirmation indicators Allow time for model to learn (100+ bars) Not financial advice - educational purposes Backtest thoroughly on your instruments ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 🏆 CONCLUSION The GMM Momentum Oscillator brings institutional-grade machine learning to retail trading. By identifying market regimes probabilistically and adapting momentum calculations accordingly, it provides: Automatic adaptation to market conditions Clear regime identification with confidence levels Smooth, professional signal generation True unsupervised machine learning This isn't just another indicator with "ML" in the name - it's a genuine implementation of Gaussian Mixture Models with the Expectation-Maximization algorithm, the same technology used in: Google's speech recognition Tesla's computer vision NASA's data analysis Wall Street risk models "Let the machine learn the market regimes. Trade with statistical confidence." ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ Developed by AlphaNatt | Machine Learning Trading Systems Version: 1.0 Algorithm: Gaussian Mixture Model with E-M Classification: Unsupervised Learning Oscillator Not financial advice. Always DYOR.
Pine Script® 인디케이터
AlphaNatt의
AI-Weighted RSI (Zeiierman)█ Overview AI-Weighted RSI (Zeiierman) is an adaptive oscillator that enhances classic RSI by applying a correlation-weighted prediction layer. Instead of looking only at RSI values directly, this indicator continuously evaluates how other price- and volume-based features (returns, volatility, volume shifts) correlate with RSI, and then weights them accordingly to project the next RSI state. The result is a smoother, forward-looking RSI framework that adapts to market conditions in real time. By leveraging feature correlation instead of static formulas, AI-Weighted RSI behaves like a lightweight learning model, adjusting its emphasis depending on which features are most aligned with RSI behavior during the current regime. █ How It Works ⚪ Feature Extraction Each bar, the script computes features: log returns, RSI itself, ATR% (volatility), volume, and volume log-change. ⚪ Correlation Screening Over a rolling learning window, it measures the correlation of each feature against RSI. The strongest relationships are ranked and selected. ⚪ Adaptive Weighting Features are standardized (z-scored), then combined using their signed correlations as weights, building a rolling, adaptive prediction of RSI. ⚪ Prediction to RSI Weight The predicted RSI is mapped back into a “weight” scale (±2 by default). Above 0 = bullish bias, below 0 = bearish bias, with color-graded fills to visualize overbought/oversold pressure. ⚪ Signal Line A smoothing option (signal length) overlays a moving average of the AI-Weighted RSI for clearer trend confirmation. █ Why AI-Weighted RSI ⚪ Adaptive to Market Regime Because the model re-evaluates correlations continuously, it naturally shifts which features dominate, sometimes volatility explains RSI best, sometimes volume, sometimes returns. ⚪ Forward-Looking Bias Instead of simply reflecting RSI, the model provides a projection, helping anticipate shifts in momentum before RSI itself flips. █ How to Use ⚪ Directional Bias Read the RSI relative to 0. Above = bullish momentum bias, below = bearish. ⚪ Overbought / Oversold Zones Shaded fills beyond +0.5 or -0.5 highlight extremes where RSI pressure often exhausts. ⚪ Divergences When price makes new highs/lows but AI-Weighted RSI fails to confirm, it often signals weakening momentum. █ Settings RSI Length: Lookback for the core RSI calculation. Signal Length: Smoothing applied to the AI-Weighted RSI output. Learning Window: Bars used for correlation learning and z-scoring. ----------------- Disclaimer The content provided in my scripts, indicators, ideas, algorithms, and systems is for educational and informational purposes only. It does not constitute financial advice, investment recommendations, or a solicitation to buy or sell any financial instruments. I will not accept liability for any loss or damage, including without limitation any loss of profit, which may arise directly or indirectly from the use of or reliance on such information. All investments involve risk, and the past performance of a security, industry, sector, market, financial product, trading strategy, backtest, or individual's trading does not guarantee future results or returns. Investors are fully responsible for any investment decisions they make. Such decisions should be based solely on an evaluation of their financial circumstances, investment objectives, risk tolerance, and liquidity needs.
Pine Script® 인디케이터
Zeiierman의
3
BUY & SELL Probability (M5..D1) - MTFMTF Probability Indicator (M5 to D1) Indicator — Dual Histogram with Buy/Sell Labels This indicator is designed to provide a probabilistic bias for bullish or bearish conditions by combining three different analytical components across multiple timeframes. The goal is to reduce noise from single-indicator signals and instead highlight confluence where trend, momentum, and strength agree. Why this combination is useful - EMA(200) Trend Filter: Identifies whether price is trading above or below a widely used long-term moving average. - MACD Momentum: Detects short-term directional momentum through line crossovers. - ADX Strength: Measures how strong the trend is, preventing signals in weak or flat markets. By combining these, the indicator avoids situations where one tool signals a trade but others do not, helping to filter out low-probability setups. How it works - Each timeframe (M5, M15, H1, H4, D1) generates its own trend, momentum, and strength score. - Scores are weighted according to user-defined importance and then aggregated into a single probability. - Proximity to recent support and resistance levels can adjust the final score, accounting for nearby barriers. - The final probability is displayed as: - Histogram (subwindow): Green bars for bullish probability >50%, red bars for bearish <50%. - On-chart labels: Showing exact buy/sell percentages on the last bar for quick reference. Inputs - EMA length (default 200), MACD settings, ADX period. - Weights for each timeframe and component (trend, momentum, strength). - Optional boost for the chart’s current timeframe. - Smoothing length for probability values. - Lookback period for support/resistance adjustment. How to use it - A green histogram above zero indicates bullish probability >50%. - A red histogram below zero indicates bearish probability >50%. - Neutral readings near 50% show low confluence and may be best avoided. - Users can adjust weights to emphasize higher or lower timeframes, depending on their trading style. Notes - This script does not guarantee profitable trades. - Best used together with price action, volume, or additional confirmation tools. - Signals are calculated only on closed bars to avoid repainting. - For testing and learning purposes — not financial advice.
Pine Script® 인디케이터
DenizTheTrader의
RSI Pivots with Divergence Overlay█ OVERVIEW The RSI Pivots with Divergence Overlay indicator is an advanced tool based on RSI, displaying dynamic bands on the price chart to simplify the identification of overbought and oversold conditions. Pivot points and divergences between them are derived from these bands, providing a comprehensive view of the market and enabling the creation of various trading strategies based on this single indicator. █ CONCEPTS Areas where RSI exits the bands are often reversal points in the market. The concept of this indicator is to highlight places where the probability of a trend reversal increases. Therefore, pivots and divergences have been added to better identify these key moments. Additionally, the bands allow viewing the market context in relation to the RSI indicator, facilitating analysis of momentum and volatility. █ KEY FEATURES Dynamic Bands and RSI Signals: The bands are calculated based on the closing price and RSI value, with dynamic scaling adjusted to market volatility. The upper band corresponds to overbought levels, the lower to oversold, and the midline is their average. The price level relative to the bands serves as a visual RSI signal, indicating potential overbought or oversold conditions. Pivot Points: The indicator identifies local price highs and lows in relation to RSI levels. The pivot level is taken from the high/low of the candle. A high pivot is detected when the high of the candle reaches a local maximum after crossing the upper RSI level (overbought), signaling a potential reversal. A low pivot appears after a local price minimum following a drop below the lower RSI level (oversold), indicating a possible uptrend reversal. The pivot length (default 2 bars) defines the search range for these extremes, meaning that with a length of 2, a potential divergence signal will appear with a 2-candle delay, as this is the minimum time required to confirm a local pivot. Pivot lines are drawn on the chart, and labels display the RSI value (from the close of the candle) and price at the detection moment. Pivot lines disappear after the detection of the next low pivot for lower lines and high pivot for upper lines, but unbreached lines or those with high volume may still serve as support or resistance levels. Divergence Detection: The indicator automatically detects divergences to predict trend changes. Bearish divergence occurs when the price forms a higher high pivot, but the RSI (from the close of the candle) is lower than in the previous pivot, indicating weakening upward momentum and a potential bearish reversal. Bullish divergence appears when the price forms a lower low pivot, but the RSI is higher, suggesting building momentum and a possible bullish reversal. Divergences are marked in pivot labels (e.g., "Bear Div" or "Bull Div") and supported by alerts upon detection. Return Signals: The indicator generates buy and sell signals based on RSI (price) returning to the bands after extreme conditions, independently of pivots and divergences. A buy signal is triggered when RSI (price) crosses above the lower level (exiting oversold), suggesting a potential price rise toward the midline or upper band. A sell signal occurs when RSI (price) falls below the upper level (exiting overbought), indicating a possible price drop toward the lower band. Signals are visualized as arrows (up/down triangles) on the chart, with customizable colors. █ CONFIGURATION The indicator offers extensive customization options: RSI Length (rsiLength): Sets the number of periods used to calculate RSI (default 14). RSI Upper Level (rsiUpper): Defines the overbought threshold (default 70). RSI Lower Level (rsiLower): Defines the oversold threshold (default 30). Band Scaling (scale): Determines the scaling multiplier for bands based on market volatility (default 15.0). SMA Length for Candle Midpoint (length): Number of periods for calculating the moving average of candle midpoints (default 200). This parameter is used to smooth price data, enabling more accurate volatility assessment and band width adjustment to market dynamics. Pivot Length (pivotLength): Sets the range (in bars) for detecting local price extremes (default 2). Pivot Label Offset (pivotLabelOffset): Multiplier for the candle range to position pivot labels (default 0.3). Show Bands (showBands): Enables/disables the display of bands on the chart. Show Fill (showFill): Enables/disables the fill between bands and the midline. Show Pivot Lines (showPivotLines): Enables/disables pivot lines on the chart. Show Pivot Labels (showPivotLabels): Enables/disables labels with RSI and price values at pivots. Show Return Signals (showReturnSignals): Enables/disables the display of buy and sell signals. Colors and Style: Customizable colors for bands, fills, pivot lines, labels, and line widths (default 1). █ USAGE The indicator performs best when combined with other technical analysis tools, such as Fibonacci levels, moving averages, or trendlines, to confirm pivot, divergence, and return signals. It enables traders to identify key reversal points, detect hidden trend weaknesses through divergences, and confirm trade entries with return signals. Usage Examples: Price bounces off a previous pivot with high volume – this increases the probability of a trend change or correction. A similar situation when RSI is outside the bands strengthens the signal. If divergence occurs in addition, we have further confirmation. This can be combined with Fibonacci levels to check if Fibo zones overlap with pivot lines – this may increase the chance of a strong price reaction. █ ALERTS The indicator supports alerts for: Buy and sell signals (RSI returning to bands). Detection of bearish and bullish divergences.
Pine Script® 인디케이터
Uncle_the_shooter의
RSI ADX Bollinger Analysis High-level purpose and design philosophy This indicator — RSI-ADX-Bollinger Analysis — is a compact, educational market-analysis toolkit that blends momentum (RSI), trend strength (ADX), volatility structure (Bollinger Bands) and simple volumetrics to provide traders a snapshot of market condition and trade idea quality. The design philosophy is explicit and layered: use each component to answer a different question about price action (momentum, conviction, volatility, participation), then combine answers to form a more robust, explainable signal. The mashup is intended for analysis and learning, not automatic execution: it surfaces the why behind signals so traders can test, learn and apply rules with risk management. ________________________________________ What each indicator contributes (component-by-component) RSI (Relative Strength Index) — role and behavior: RSI measures short-term momentum by comparing recent gains to recent losses. A high RSI (near or above the overbought threshold) indicates strong recent buying pressure and potential exhaustion if price is extended. A low RSI (near or below the oversold threshold) indicates strong recent selling pressure and potential exhaustion or a value area for mean-reversion. In this dashboard RSI is used as the primary momentum trigger: it helps identify whether price is locally over-extended on the buy or sell side. ADX (Average Directional Index) — role and behavior: ADX measures trend strength independently of direction. When ADX rises above a chosen threshold (e.g., 25), it signals that the market is trending with conviction; ADX below the threshold suggests range or weak trend. Because patterns and momentum signals perform differently in trending vs. ranging markets, ADX is used here as a filter: only when ADX indicates sufficient directional strength does the system treat RSI+BB breakouts as meaningful trade candidates. Bollinger Bands — role and behavior: Bollinger Bands (20-period basis ± N standard deviations) show volatility envelope and relative price position vs. a volatility-adjusted mean. Price outside the upper band suggests pronounced extension relative to recent volatility; price outside the lower band suggests extended weakness. A band expansion (increasing width) signals volatility breakout potential; contraction signals range-bound conditions and potential squeeze. In this dashboard, Bollinger Bands provide the volatility/structural context: RSI extremes plus price beyond the band imply a stronger, volatility-backed move. Volume split & basic MA trend — role and behavior: Buy-like and sell-like volume (simple heuristic using close>open or closeopen) or sell-like (close1.2 for validation and compare win rate and expectancy. 4. TF alignment: Accept signals only when higher timeframe (e.g., 4h) trend agrees — compare results. 5. Parameter sensitivity: Vary RSI threshold (70/30 vs 80/20), Bollinger stddev (2 vs 2.5), and ADX threshold (25 vs 30) and measure stability of results. These exercises teach both statistical thinking and the specific failure modes of the mashup. ________________________________________ Limitations, failure modes and caveats (explicit & teachable) • ADX and Bollinger measures lag during fast-moving news events — signals can be late or wrong during earnings, macro shocks, or illiquid sessions. • Volume classification by open/close is a heuristic; it does not equal TAPEDATA, footprint or signed volume. Use it as supportive evidence, not definitive proof. • RSI can remain overbought or oversold for extended stretches in persistent trends — relying solely on RSI extremes without ADX or BB context invites large drawdowns. • Small-cap or low-liquidity instruments yield noisy band behavior and unreliable volume ratios. Being explicit about these limitations is a strong point in a TradingView description — it demonstrates transparency and educational intent. ________________________________________ Originality & mashup justification (text you can paste) This script intentionally combines classical momentum (RSI), volatility envelope (Bollinger Bands) and trend-strength (ADX) because each indicator answers a different and complementary question: RSI answers is price locally extreme?, Bollinger answers is price outside normal volatility?, and ADX answers is the market moving with conviction?. Volume participation then acts as a practical check for real market involvement. This combination is not a simple “indicator mashup”; it is a designed ensemble where each element reduces the others’ failure modes and together produce a teachable, testable signal framework. The script’s purpose is educational and analytical — to show traders how to interpret the interplay of momentum, volatility, and trend strength. ________________________________________ TradingView publication guidance & compliance checklist To satisfy TradingView rules about mashups and descriptions, include the following items in your script description (without exposing source code): 1. Purpose statement: One or two lines describing the script’s objective (educational multi-indicator market overview and idea filter). 2. Component list: Name the major modules (RSI, Bollinger Bands, ADX, volume heuristic, SMA trend checks, signal tracking) and one-sentence reason for each. 3. How they interact: A succinct non-code explanation: “RSI finds momentum extremes; Bollinger confirms volatility expansion; ADX confirms trend strength; all three must align for a BUY/SELL.” 4. Inputs: List adjustable inputs (RSI length and thresholds, BB length & stddev, ADX threshold & smoothing, volume MA, table position/size). 5. Usage instructions: Short workflow (check TF alignment → confirm participation → define stop & R:R → backtest). 6. Limitations & assumptions: Explicitly state volume is approximated, ADX has lag, and avoid promising guaranteed profits. 7. Non-promotional language: No external contact info, ads, claims of exclusivity or guaranteed outcomes. 8. Trademark clause: If you used trademark symbols, remove or provide registration proof. 9. Risk disclaimer: Add the copy-ready disclaimer below. This matches TradingView’s request for meaningful descriptions that explain originality and inter-component reasoning. ________________________________________ Copy-ready short publication description (paste into TradingView) Advanced RSI-ADX-Bollinger Market Overview — educational multi-indicator dashboard. This script combines RSI (momentum extremes), Bollinger Bands (volatility envelope and band expansion), ADX (trend strength), simple SMA trend bias and a basic buy/sell volume heuristic to surface high-quality idea candidates. Signals require alignment of momentum, volatility expansion and rising ADX; volume participation is displayed to support signal confidence. Inputs are configurable (RSI length/levels, BB length/stddev, ADX length/threshold, volume MA, display options). This tool is intended for analysis and learning — not for automated execution. Users should back test and apply robust risk management. Limitations: volume classification here is a heuristic (close>open), ADX and BB measures lag in fast news events, and results vary by instrument liquidity. ________________________________________ Copy-ready risk & misuse disclaimer (paste into description or help file) This script is provided for educational and analytical purposes only and does not constitute financial or investment advice. It does not guarantee profits. Indicators are heuristics and may give false or late signals; always back test and paper-trade before using real capital. The author is not responsible for trading losses resulting from the use or misuse of this indicator. Use proper position sizing and risk controls. ________________________________________ Risk Disclaimer: This tool is provided for education and analysis only. It is not financial advice and does not guarantee returns. Users assume all risk for trades made based on this script. Back test thoroughly and use proper risk management.
Pine Script® 인디케이터
aiTrendview-Charting-System의
Multi-RSI with Stochastic Oscillator - flack0xA sophisticated momentum analysis tool combining 4 customizable RSI oscillators with an innovative Close/Close Stochastic implementation. Designed for traders seeking comprehensive momentum insights across multiple timeframes in a single, organized indicator. Key Features: 4 Independent RSI Oscillators with default periods: 2, 3, 9, 27 Innovative Close/Close Stochastic - Compares closing prices to closing price ranges (not high/low) Complete Customization - Individual control over periods, colors, line widths, and visibility Reference Levels - Customizable overbought (70), oversold (30), and midline (50) levels Smart Alert System - Crossover notifications for key momentum shifts Unique Close/Close Stochastic Methodology: Unlike traditional Stochastic oscillators that use high/low ranges. Benefits of Close/Close Approach: Eliminates Gap Noise - Ignores overnight gaps and intraday wicks Smoother Signals - Reduces whipsaws common in traditional Stochastic Position-Relevant - Focuses on actual settlement prices traders care about Cleaner Momentum Reading - Pure closing price momentum without intraday volatility
Pine Script® 인디케이터
flack0x의
Hurst Momentum Oscillator | AlphaNattHurst Momentum Oscillator | AlphaNatt An adaptive oscillator that combines the Hurst Exponent - which identifies whether markets are trending or mean-reverting - with momentum analysis to create signals that automatically adjust to market regime. "The Hurst Exponent reveals a hidden truth: markets aren't always trending. This oscillator knows when to ride momentum and when to fade it." ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 📐 THE MATHEMATICS Hurst Exponent (H): Measures the long-term memory of time series: H > 0.5: Trending (persistent) behavior H = 0.5: Random walk H < 0.5: Mean-reverting behavior Originally developed for analyzing Nile river flooding patterns, now used in: Fractal market analysis Network traffic prediction Climate modeling Financial markets The Innovation: This oscillator multiplies momentum by the Hurst coefficient: When trending (H > 0.5): Momentum is amplified When mean-reverting (H < 0.5): Momentum is reduced Result: Adaptive signals based on market regime ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 💎 KEY ADVANTAGES Regime Adaptive: Automatically adjusts to trending vs ranging markets False Signal Reduction: Reduces momentum signals in mean-reverting markets Trend Amplification: Stronger signals when trends are persistent Mathematical Edge: Based on fractal dimension analysis No Repainting: All calculations on historical data ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 📊 TRADING SIGNALS Visual Interpretation: Cyan zones: Bullish momentum in trending market Magenta zones: Bearish momentum or mean reversion Background tint: Blue = trending, Pink = mean-reverting Gradient intensity: Signal strength Trading Strategies: 1. Trend Following: Trade momentum signals when background is blue (trending) 2. Mean Reversion: Fade extreme readings when background is pink 3. Regime Transition: Watch for background color changes as early warning ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 🎯 OPTIMAL USAGE Best Conditions: Strong trending markets (crypto bull runs) Clear ranging markets (forex sessions) Regime transitions Multi-timeframe analysis Market Applications: Crypto: Excellent for identifying trend persistence Forex: Detects when pairs are ranging Stocks: Identifies momentum stocks Commodities: Catches persistent trends ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ Developed by AlphaNatt | Fractal Market Analysis Version: 1.0 Classification: Adaptive Regime Oscillator Not financial advice. Always DYOR.
Pine Script® 인디케이터
AlphaNatt의
1
TRAPPER TRENDLINES — RSIBuilds dynamic RSI trendlines by connecting the two most recent confirmed RSI swing points (highs→highs for resistance, lows→lows for support). Includes optional channel shading for the 30–70 zone, an RSI moving average, clean break alerts, and simple bullish/bearish divergence alerts versus price. How it works RSI pivots: A point on RSI is a swing high/low only if it is the most extreme value compared with a set number of bars on the left and the right (the Pivot Lookback). RSI trendlines: Resistance connects the last two confirmed RSI swing highs. Support connects the last two confirmed RSI swing lows. Lines can be Full Extend (update into the future) or Pivot Only. Channel block: Optional fill of the 30–70 range for fast visual context. Alerts: Breaks of RSI support/resistance trendlines. Basic bullish/bearish RSI divergences versus price pivots. Inputs RSI RSI Length: Default 14 (standard). Pivot Lookback: Bars to the left/right required to confirm an RSI swing. Overbought / Oversold: 70 / 30 by default. Line Extension: Full Extend or Pivot Only. Visuals Show RSI Moving Average / Signal Length: Optional smoothing line on RSI. RSI/Signal colors: Customize plot colors. Show 30–70 Channel Block: Toggle the middle-zone fill. Tint pane background when RSI in channel: Optional subtle background when RSI is between OB/OS. Divergences & Alerts Enable RSI TL Break Alerts: Alert conditions for RSI line breaks. Enable Divergence Alerts: Bullish/Bearish divergence alerts versus price. Pairing with price for confluence/divergence For accurate confluence and clearer divergences, align this RSI tool with your price trendline tool (for example, TRAPPER TRENDLINES — PRICE): Set RSI Pivot Lookback equal to the Pivot Left/Right size used on price. Example: Price uses Pivot Left = 50 and Pivot Right = 50 → set RSI Pivot Lookback = 50. Keep RSI Length = 14 and OB/OS = 70/30 unless you have a specific edge. Interpretation: Confluence: Price reacts at its trendline while RSI reacts at its own line in the same direction. Divergence: Price makes a higher high while RSI makes a lower high (bearish), or price makes a lower low while RSI makes a higher low (bullish), using matched pivot windows. Suggested settings Higher timeframes (4H / 1D / 1W): Pivot Lookback = 50; optional RSI MA length 14; channel block ON. Intraday (15m / 30m / 1H): Pivot Lookback = 30; optional RSI MA length 14. Always mirror your price pivot size to this RSI Pivot Lookback for consistent swings. Reading the signals RSI trendline touch/hold: Momentum reacting at structure; look for confluence with price levels. RSI Trendline Break Up / Down: Momentum shift; consider price structure and retests. Bullish/Bearish Divergence: Confirm only when pivots are matched and the new swing is confirmed. Notes & limitations Pivots require future bars to confirm by design; trendlines update as new swings confirm. Divergence logic compares RSI pivots to price pivots with the same lookback; mismatched windows can produce false positives. No strategy entries/exits or performance claims are provided. This is an analytical tool. Alerts (titles/messages) RSI: Trendline Break Up — “RSI broke falling resistance line.” RSI: Trendline Break Down — “RSI broke rising support line.” RSI: Bullish Divergence — “Bullish RSI divergence confirmed.” RSI: Bearish Divergence — “Bearish RSI divergence confirmed.” Quick start Add the indicator to a separate pane. Set Pivot Lookback to match your price tool’s pivot size (e.g., 50). Optionally toggle the RSI MA and Channel Block for clarity. Enable alerts if you want notifications on RSI line breaks and divergences. Use with TRAPPER TRENDLINES — PRICE or any price-based trendline tool for confluence/divergence analysis. Compliance This script is for educational purposes only and does not constitute financial advice. Trading involves risk. Past performance does not guarantee future results. No performance claims are made.
Pine Script® 인디케이터
RAMS-offthecharts의
2
Simplified Market ForecastSimplified Market Forecast Indicator This indicator pairs nicely with the Contrarian 100 MA and can be located here: Overview The "Simplified Market Forecast" (SMF) indicator is a streamlined technical analysis tool designed for traders to identify potential buy and sell opportunities based on a momentum-based oscillator. By analyzing price movements relative to a defined lookback period, SMF generates clear buy and sell signals when the oscillator crosses customizable threshold levels. This indicator is versatile, suitable for various markets (e.g., forex, stocks, cryptocurrencies), and optimized for daily timeframes, though it can be adapted to other timeframes with proper testing. Its intuitive design and visual cues make it accessible for both novice and experienced traders. How It Works The SMF indicator calculates a momentum oscillator based on the price’s position within a specified range over a user-defined lookback period. It then smooths this value to reduce noise and plots the result as a line in a separate lower pane. Buy and sell signals are generated when the smoothed oscillator crosses above a user-defined buy level or below a user-defined sell level, respectively. These signals are visualized as triangles either on the main chart or in the lower pane, with a table displaying the current ticker and oscillator value for quick reference. Key Components Momentum Oscillator: The indicator measures the price’s position relative to the highest high and lowest low over a specified period, normalized to a 0–100 scale. Signal Generation: Buy signals occur when the oscillator crosses above the buy level (default: 15), indicating potential oversold conditions. Sell signals occur when the oscillator crosses below the sell level (default: 85), suggesting potential overbought conditions. Visual Aids: The indicator includes customizable horizontal lines for buy and sell levels, shaded zones for clarity, and a table showing the ticker and current oscillator value. Mathematical Concepts Oscillator Calculation: The indicator uses the following formula to compute the raw oscillator value: c1I = close - lowest(low, medLen) c2I = highest(high, medLen) - lowest(low, medLen) fastK_I = (c1I / c2I) * 100 The result is smoothed using a 5-period Simple Moving Average (SMA) to produce the final oscillator value (inter). Signal Logic: A buy signal is triggered when the smoothed oscillator crosses above the buy level (ta.crossover(inter, buyLevel)). A sell signal is triggered when the smoothed oscillator crosses below the sell level (ta.crossunder(inter, sellLevel)). Entry and Exit Rules Buy Signal (Blue Triangle): Triggered when the oscillator crosses above the buy level (default: 15), indicating a potential oversold condition and a buying opportunity. The signal appears as a blue triangle either below the price bar (if plotted on the main chart) or at the bottom of the lower pane. Sell Signal (White Triangle): Triggered when the oscillator crosses below the sell level (default: 85), indicating a potential overbought condition and a selling opportunity. The signal appears as a white triangle either above the price bar (if plotted on the main chart) or at the top of the lower pane. Exit Rules: Traders can exit positions when an opposite signal occurs (e.g., exit a buy on a sell signal) or based on additional technical analysis tools (e.g., support/resistance, trendlines). Always apply proper risk management. Recommended Usage The SMF indicator is optimized for the daily timeframe but can be adapted to other timeframes (e.g., 1H, 4H) with careful testing. It performs best in markets with clear momentum shifts, such as trending or range-bound conditions. Traders should: Backtest the indicator on their chosen asset and timeframe to validate signal reliability. Combine with other indicators (e.g., moving averages, support/resistance) or price action for confirmation. Adjust the lookback period and buy/sell levels to suit market volatility and trading style. Customization Options Intermediate Length: Adjust the lookback period for the oscillator calculation (default: 31 bars). Buy/Sell Levels: Customize the threshold levels for buy (default: 15) and sell (default: 85) signals. Colors: Modify the colors of the oscillator line, buy/sell signals, and threshold lines. Signal Display: Toggle whether signals appear on the main chart or in the lower pane. Visual Aids: The indicator includes dotted horizontal lines at the buy (green) and sell (red) levels, with shaded zones between 0–buy level (green) and sell level–100 (red) for clarity. Ticker Table: A table in the top-right corner displays the current ticker and oscillator value (in percentage), with customizable colors. Why Use This Indicator? The "Simplified Market Forecast" indicator provides a straightforward, momentum-based approach to identifying potential reversals in overbought or oversold markets. Its clear signals, customizable settings, and visual aids make it easy to integrate into various trading strategies. Whether you’re a swing trader or a day trader, SMF offers a reliable tool to enhance decision-making and improve market timing. Tips for Users Test the indicator thoroughly on your chosen asset and timeframe to optimize settings. Use in conjunction with other technical tools for stronger trade confirmation. Adjust the buy and sell levels based on market conditions (e.g., lower levels for less volatile markets). Monitor the ticker table for real-time oscillator values to gauge market momentum. Happy trading with the Simplified Market Forecast indicator!
Pine Script® 인디케이터
chuckaschultz의
Fisher Volume Transform | AlphaNattFisher Volume Transform | AlphaNatt A powerful oscillator that applies the Fisher Transform - converting price into a Gaussian normal distribution - while incorporating volume weighting to identify high-probability reversal points with institutional participation. "The Fisher Transform reveals what statistics professors have known for decades: when you transform market data into a normal distribution, turning points become crystal clear." ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 🎲 THE MATHEMATICS Fisher Transform Formula: The Fisher Transform converts any bounded dataset into a Gaussian distribution: y = 0.5 × ln((1 + x) / (1 - x)) Where x is normalized price (-1 to 1 range) Why This Matters: Market extremes become statistically identifiable Turning points are amplified and clarified Removes the skew from price distributions Creates nearly instantaneous signals at reversals Volume Integration: Unlike standard Fisher Transform, this version weights price by relative volume: High volume moves get more weight Low volume moves get filtered out Identifies institutional participation Reduces false signals from retail chop ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 💎 KEY ADVANTAGES Statistical Edge: Transforms price into normal distribution where extremes are mathematically defined Volume Confirmation: Only signals with volume support Early Reversal Detection: Fisher Transform amplifies turning points Clean Signals: Gaussian distribution reduces noise No Lag: Mathematical transformation, not averaging ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ ⚙️ SETTINGS OPTIMIZATION Fisher Period (5-30): 5-9: Very sensitive, many signals 10: Default - balanced sensitivity 15-20: Moderate smoothing 25-30: Major reversals only Volume Weight (0.1-1.0): 0.1-0.3: Minimal volume influence 0.5-0.7: Balanced price/volume 0.7: Default - strong volume weight 0.8-1.0: Volume dominant ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 📊 TRADING SIGNALS Primary Signals: Zero Cross Up: Bullish momentum shift Zero Cross Down: Bearish momentum shift Signal Line Cross: Early reversal warning Extreme Readings (±75): Potential reversal zones Visual Interpretation: Cyan zones: Bullish momentum Magenta zones: Bearish momentum Gradient intensity: Strength of move Histogram: Raw momentum power ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 🎯 OPTIMAL USAGE Best Market Conditions: Range-bound markets (reversals clear) High volume periods Major support/resistance levels Divergence hunting Trading Strategies: 1. Extreme Reversal: Enter when oscillator exceeds ±75 and reverses 2. Zero Line Momentum: Trade crosses of zero line with volume confirmation 3. Signal Line Strategy: Early entry on signal line crosses 4. Divergence Trading: Price makes new high/low but Fisher doesn't ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ Developed by AlphaNatt | Quantitative Trading Systems Version: 1.0 Classification: Statistical Transform Oscillator Not financial advice. Always DYOR.
Pine Script® 인디케이터
AlphaNatt의
Supertrend [TradingConToto]Supertrend — ADX/DI + EMA Gap + Breakout (with Mobile UI) What makes it original Supertrend combines trend strength (ADX/DI), multi-timeframe bias (EMA63 and EMA 200D equivalent), a structural filter based on the distance between EMA2400 and EMA4800 expressed in ATR units, and a momentum confirmation through a previous high breakout. This is not a random mashup — it’s a sequence of filters designed to reduce trades in ranging markets and prioritize mature trends: Direction: +DI > -DI (trend led by buyers). Strength: ADX > mean(ADX) (avoids weak, choppy phases). Short-term bias: Close > EMA63. Long-term bias: Close > EMA4800 ≈ EMA200 daily on H1. Momentum: Close > High (immediate breakout). Structure: (EMA2400 − EMA4800) > k·ATR (ensures separation in ATR units, filters out flat phases). Entries & exits Entry: when all six conditions are met and no open position exists. Exit: if +DI < -DI or Close < EMA63. Visuals: EMA63 is painted green while in position and red otherwise, with a supertrend-style band; “BUY” labels appear below the green band and “SELL” labels above the red band. UI: includes a compact table (mobile-friendly) showing the state of each condition. Default parameters used in this publication Initial capital: 10,000 Position size: 10% of equity (≤10% per trade is considered sustainable). Commission: 0.01% per side (adjust to your broker/market). Slippage: 1 tick Pyramiding: 0 (only one position at a time) Adjust commission/slippage to match your market. For US equities, commissions are often per share; for spot crypto, 0.10–0.20% total is common. I publish with 0.01% per side as a conservative example to avoid overestimating results. Recommended backtest dataset Timeframe: H1 Multi-cycle window (e.g. 2015–today) Symbols with high liquidity (e.g. NASDAQ-100 large caps, or BTC/ETH spot) to generate 100+ trades. Avoid cherry-picked short windows. Why each filter matters +DI > -DI + ADX > mean: reduce counter-trend trades and weak signals. Close > EMA63 + Close > EMA4800: enforce trend alignment in short and long horizons. Breakout High : requires immediate momentum, avoids early entries. EMA gap in ATR units: blocks flat or compressed structures where EMA200D aligns with price. Limitations The breakout filter may skip healthy pullbacks; the design prioritizes continuation over perfect entry price. No fixed trailing stop/TP; exits depend on trend degradation via DI/EMA63. Results vary with real costs (commissions, slippage, funding). Adjust defaults to your broker. How to use Apply it on a clean chart (no other indicators when publishing). Keep in mind the default parameters above; if you change them, mention it in your notes and use the same values in the Strategy Tester. Ensure your dataset produces 100+ trades for statistical validity.
Pine Script™ 전략
toto_scalper_23의
1
Savitzky-Golay Hampel Filter | AlphaNattSavitzky-Golay Hampel Filter | AlphaNatt A revolutionary indicator combining NASA's satellite data processing algorithms with robust statistical outlier detection to create the most scientifically advanced trend filter available on TradingView. "This is the same mathematics that processes signals from the Hubble Space Telescope and analyzes data from the Large Hadron Collider - now applied to financial markets." ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 🚀 SCIENTIFIC PEDIGREE Savitzky-Golay Filter Applications: NASA: Satellite telemetry and space probe data processing CERN: Particle physics data analysis at the LHC Pharmaceutical: Chromatography and spectroscopy analysis Astronomy: Processing signals from radio telescopes Medical: ECG and EEG signal processing Hampel Filter Usage: Aerospace: Cleaning sensor data from aircraft and spacecraft Manufacturing: Quality control in precision engineering Seismology: Earthquake detection and analysis Robotics: Sensor fusion and noise reduction ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 🧬 THE MATHEMATICS 1. Savitzky-Golay Filter The SG filter performs local polynomial regression on data points: Fits a polynomial of degree n to a sliding window of data Evaluates the polynomial at the center point Preserves higher moments (peaks, valleys) unlike moving averages Maintains derivative information for true momentum analysis Originally published in Analytical Chemistry (1964) Mathematical Properties: Optimal smoothing in the least-squares sense Preserves statistical moments up to polynomial order Exact derivative calculation without additional lag Superior frequency response vs traditional filters 2. Hampel Filter A robust outlier detector based on Median Absolute Deviation (MAD): Identifies outliers using robust statistics Replaces spurious values with polynomial-fitted estimates Resistant to up to 50% contaminated data MAD is 1.4826 times more robust than standard deviation Outlier Detection Formula: |x - median| > k × 1.4826 × MAD Where k is the threshold parameter (typically 3 for 99.7% confidence) ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 💎 WHY THIS IS SUPERIOR vs Moving Averages: Preserves peaks and valleys (critical for catching tops/bottoms) No lag penalty for smoothness Maintains derivative information Polynomial fitting > simple averaging vs Other Filters: Outlier immunity (Hampel component) Scientifically optimal smoothing Preserves higher-order features Used in billion-dollar research projects Unique Advantages: Feature Preservation: Maintains market structure while smoothing Spike Immunity: Ignores false breakouts and stop hunts Derivative Accuracy: True momentum without additional indicators Scientific Validation: 60+ years of academic research ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ ⚙️ PARAMETER OPTIMIZATION 1. Polynomial Order (2-5) 2 (Quadratic): Maximum smoothing, gentle curves 3 (Cubic): Balanced smoothing and responsiveness (recommended) 4-5 (Higher): More responsive, preserves more features 2. Window Size (7-51) Must be odd number Larger = smoother but more lag Formula: 2×(desired smoothing period) + 1 Default 21 = analyzes 10 bars each side 3. Hampel Threshold (1.0-5.0) 1.0: Aggressive outlier removal (68% confidence) 2.0: Moderate outlier removal (95% confidence) 3.0: Conservative outlier removal (99.7% confidence) (default) 4.0+: Only extreme outliers removed 4. Final Smoothing (1-7) Additional WMA smoothing after filtering 1 = No additional smoothing 3-5 = Recommended for most timeframes 7 = Ultra-smooth for position trading ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 📊 TRADING STRATEGIES Signal Recognition: Cyan Line: Bullish trend with positive derivative Pink Line: Bearish trend with negative derivative Color Change: Trend reversal with polynomial confirmation 1. Trend Following Strategy Enter when price crosses above cyan filter Exit when filter turns pink Use filter as dynamic stop loss Best in trending markets 2. Mean Reversion Strategy Enter long when price touches filter from below in uptrend Enter short when price touches filter from above in downtrend Exit at opposite band or filter color change Excellent for range-bound markets 3. Derivative Strategy (Advanced) The SG filter preserves derivative information Acceleration = second derivative > 0 Enter on positive first derivative + positive acceleration Exit on negative second derivative (momentum slowing) ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 📈 PERFORMANCE CHARACTERISTICS Strengths: Outlier Immunity: Ignores stop hunts and flash crashes Feature Preservation: Catches tops/bottoms better than MAs Smooth Output: Reduces whipsaws significantly Scientific Basis: Not curve-fitted or optimized to markets Considerations: Slight lag in extreme volatility (all filters have this) Requires odd window sizes (mathematical requirement) More complex than simple moving averages Best with liquid instruments ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 🔬 SCIENTIFIC BACKGROUND Savitzky-Golay Publication: "Smoothing and Differentiation of Data by Simplified Least Squares Procedures" - Abraham Savitzky & Marcel Golay - Analytical Chemistry, Vol. 36, No. 8, 1964 Hampel Filter Origin: "Robust Statistics: The Approach Based on Influence Functions" - Frank Hampel et al., 1986 - Princeton University Press These techniques have been validated in thousands of scientific papers and are standard tools in: NASA's Jet Propulsion Laboratory European Space Agency CERN (Large Hadron Collider) MIT Lincoln Laboratory Max Planck Institutes ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 💡 ADVANCED TIPS News Trading: Lower Hampel threshold before major events to catch spikes Scalping: Use Order=2 for maximum smoothness, Window=11 for responsiveness Position Trading: Increase Window to 31+ for long-term trends Combine with Volume: Strong trends need volume confirmation Multiple Timeframes: Use daily for trend, hourly for entry Watch the Derivative: Filter color changes when first derivative changes sign ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ ⚠️ IMPORTANT NOTICES Not financial advice - educational purposes only Past performance does not guarantee future results Always use proper risk management Test settings on your specific instrument and timeframe No indicator is perfect - part of complete trading system ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 🏆 CONCLUSION The Savitzky-Golay Hampel Filter represents the pinnacle of scientific signal processing applied to financial markets. By combining polynomial regression with robust outlier detection, traders gain access to the same mathematical tools that: Guide spacecraft to other planets Detect gravitational waves from black holes Analyze particle collisions at near light-speed Process signals from deep space This isn't just another indicator - it's rocket science for trading . "When NASA needs to separate signal from noise in billion-dollar missions, they use these exact algorithms. Now you can too." ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ Developed by AlphaNatt Version: 1.0 Release: 2025 Pine Script: v6 "Where Space Technology Meets Market Analysis" Not financial advice. Always DYOR
Pine Script® 인디케이터
AlphaNatt의
3
Swing Oracle Stock// (\_/) // ( •.•) // (")_(") 📌 Swing Oracle Stock – Professional Cycle & Trend Detection Indicator The Swing Oracle Stock is an advanced market analysis tool designed to highlight price cycles, trend shifts, and key trading zones with precision. It combines trendline dynamics, normalized oscillators, and multi-timeframe confirmation into a single comprehensive indicator. 🔑 Key Features NDOS (Normalized Dynamic Oscillator System): Measures price strength relative to recent highs and lows to detect overbought, neutral, and oversold zones. Dynamic Trendline (EMA8 or SMA231): Flexible source selection for adapting to different trading styles (scalping vs. swing). Multi-Timeframe H1 Confirmation: Adds higher-timeframe validation to improve signal reliability. Automated Buy & Sell Signals: Triggered only on significant crossovers above/below defined levels. Weekly Cycles (7-day M5 projection): Tracks recurring time-based market cycles to anticipate reversal points. Intuitive Visualization: Colored zones (high, low, neutral) for quick market context. Optional background and candlestick coloring for better clarity. Multi-Timeframe Cross Table: Automatically compares SMA50 vs. EMA200 across multiple timeframes (1m → 4h), showing clear status: ⭐️⬆️ UP = bullish trend confirmation 💀⬇️ Drop = bearish trend confirmation 📊 Built-in Statistical Tools Normalized difference between short and long EMA. Projected normalized mean levels plotted directly on the main chart. Dynamic analysis of price distance from SMA50 to capture market “waves.” 🎯 Use Cases Spot trend reversals with multi-timeframe confirmation. Identify powerful breakout and breakdown zones. Time entries and exits based on trend + cycle confluence. Enhance market timing for swing trades, scalps, or long-term positions. ⚡ Swing Oracle Stock brings together cycle detection, oscillator normalization, and multi-timeframe confirmation into one streamlined indicator for traders who want a professional edge.
Pine Script® 인디케이터
FollowtheWhiteRabbitz의
Momentum Index [BigBeluga]The Momentum Index is an innovative indicator designed to measure the momentum of price action by analyzing the distribution of positive and negative momentum values over a defined period. By incorporating delta-based calculations and smoothing techniques, it provides traders with a clear and actionable representation of market momentum dynamics. 🔵 Key Features: Delta-Based Momentum Analysis: Calculates the momentum of price by comparing its current state to its value from a defined number of bars back. Inside a loop, it evaluates whether momentum values are above or below zero, producing a delta value that reflects the net momentum direction and intensity. Double EMA Smoothing: Smooths the raw delta-based momentum values with a double EMA filter, reducing noise and providing a clearer trend signal. tmi(len) => sum = 0.0 sum1 = 0.0 above = 0.0 below = 0.0 src_ = src - src for i = 0 to len sum := sum + (src_ > nz(src_ ) ? 1 : -1) sum1 := sum1 + (sum > 0 ? 1 : -1) sum1 := emaEma(sum1, 10) for i = 1 to len above := above + (sum1 > 0 ? 1 : 0) below := below + (sum1 > 0 ? 0 : 1) Directional Momentum Signals: Generates momentum shift signals and displays them on both the oscillator and the main chart: - △ Aqua Triangles: Represent upward momentum shifts. - ▽ Red Triangles: Represent downward momentum shifts. Dynamic Gradient Display: Highlights momentum zones with gradient fills: - Aqua shades for positive momentum (above zero). - Red shades for negative momentum (below zero). Dashboard Display: A dashboard summarizing the count of momentum values above and below zero for the defined period (Sentiment Length e.g. 100), helping traders assess market sentiment at a glance. 🔵 How It Works: The indicator takes price momentum as its source and evaluates the number of momentum values above and below zero within a defined period. The delta calculation aggregates this information, providing a net representation of the prevailing market momentum. A double EMA filter is applied to the delta values, smoothing the momentum line and enhancing signal clarity. Momentum shifts are highlighted with visual signals on the oscillator and price chart, while the gradient display provides a visual representation of intensity. 🔵 Use Cases: Momentum Tracking: Identify whether market momentum is predominantly bullish or bearish. Signal Confirmation: Use chart-based signals to confirm potential trend reversals or continuation. Analyze Market Strength: Leverage the dashboard to quickly assess the distribution of momentum over the chosen period. Overbought/Oversold Conditions: Utilize gradient zones to detect areas of momentum extremes and possible price exhaustion. Momentum Index offers a refined approach to analyzing momentum dynamics, combining delta-based calculations with smoothing techniques and intuitive visuals, making it an essential tool for traders looking to anticipate market movements effectively.
Pine Script® 인디케이터
BigBeluga의
4