Mulakan

Cari dalam skrip untuk "ai"

AI Smart Money Profile v4.6 # 🕉️ AI Smart Money Profile v4.6 **by Shiv Shakti Algo Systems** AI Smart Money Profile v4.6 is a **professional all-in-one trading indicator** designed to combine **Smart Money Concepts (SMC)**, **Market Profile**, **ICT concepts**, and **AI-based trend confirmation** into a single, powerful system. This indicator is built for traders who want **structure-based trading**, **high-confluence setups**, and **clear visual guidance** without chart clutter. --- ## 🔥 Key Features ### 📊 Market Profile * Daily / Weekly / Monthly Market Profile * **POC (Point of Control)**, **VAH (Value Area High)**, **VAL (Value Area Low)** * Historical & Live Value Areas * Session bias visualization ### 🎯 Smart Money Concepts (SMC) * **BOS (Break of Structure)** * **ChoCH (Change of Character)** * Liquidity Sweeps (Buy-side & Sell-side) * Equal Highs & Equal Lows detection ### 📦 Volume Order Blocks * Volume-based Bullish & Bearish Order Blocks * Wick / Close mitigation options * Automatic removal of mitigated blocks ### ⚡ Fair Value Gaps (FVG) * Bullish & Bearish FVG detection * Auto-removal after fill or expiry * Adjustable minimum FVG size ### 🎓 ICT Concepts * **OTE (Optimal Trade Entry) Zones** * Structure-aligned premium & discount logic ### 🤖 Smart Trend AI (NEW in v4.6) * Fusion of **UT Bot + Supertrend** * Signals only when **both indicators agree** * Confirmed BUY / SELL labels (non-repainting) * Full candle coloring (body + wick) ### 📈 EMA Trend System * EMA 20 / 50 / 200 * Golden Cross & Death Cross signals * EMA trend direction shown in dashboard ### 💧 Liquidity Zones * Buy-Side Liquidity (BSL) * Sell-Side Liquidity (SSL) * Auto-detection and sweep tracking ### 📊 RSI Momentum * Positive & Negative momentum labels * Trend-aligned RSI filtering ### 🕯️ Candlestick Patterns * Marubozu (Bullish / Bearish) * Engulfing patterns * ATR-based label positioning ### 🎯 6-Point Confluence Signal Engine Signals are generated using: 1. Market Profile position 2. Market Structure (SMC) 3. Order Block presence 4. Fair Value Gap 5. OTE Zone 6. Liquidity Sweep Only **high-probability, multi-confirmation setups** are highlighted. ### 📊 Smart Dashboard * Market Structure bias * Trend direction * Confluence scores * OB, FVG, OTE, Liquidity & AI trend status * Clean and professional UI --- ## 🧠 HOW TO USE (STEP-BY-STEP) ### 1️⃣ Determine Market Bias (Top-Down) * Check **Market Structure (SMC)**: * Bullish = Higher Highs & Higher Lows * Bearish = Lower Highs & Lower Lows * Use **EMA 20 / 50 / 200** alignment: * EMA20 > EMA50 > EMA200 → Bullish bias * EMA20 < EMA50 < EMA200 → Bearish bias * Confirm bias using **Smart Trend AI** (Green = Bullish, Red = Bearish) --- ### 2️⃣ Identify High-Probability Zones Look for price interaction with: * **Value Area (VAH / VAL / POC)** * **Volume Order Blocks** * **Fair Value Gaps (FVG)** * **OTE Zones** * **Liquidity Levels (BSL / SSL)** 👉 Best trades happen when **multiple zones overlap**. --- ### 3️⃣ Wait for Liquidity & Structure Confirmation * Price sweeps **liquidity** (BSL or SSL) * Market prints **BOS or ChoCH** * Confirms direction with bullish or bearish candle This avoids early or emotional entries. --- ### 4️⃣ Confirm with AI & Momentum * **Smart Trend AI** must agree with trade direction * **RSI Momentum**: * Positive = bullish strength * Negative = bearish strength * Avoid trades when AI shows “MIX” or RSI is neutral --- ### 5️⃣ Enter Trade * Use **BUY / SELL labels** only when: * Confluence score ≥ minimum setting * Candle closes with structure confirmation * Entry can be taken: * At candle close, or * On pullback into OB / FVG --- ### 6️⃣ Risk Management (Very Important) * Always use **Stop Loss**: * Below swing low (BUY) * Above swing high (SELL) * Risk only **1–2% per trade** * Targets: * Previous high/low * Liquidity levels * Opposite Value Area --- ## ⚙️ Recommended Settings * Timeframes: **5m, 15m, 30m, 1H** * Works best on: * Indices * Forex * Crypto * Enable **ATR filter** for volatile markets --- ## ⚠️ DISCLAIMER (IMPORTANT) ⚠️ **DISCLAIMER:** This indicator is provided for **educational and informational purposes only**. It does **NOT** constitute financial advice, investment advice, or trading recommendations. Trading in financial markets involves **substantial risk**, and you may lose part or all of your capital. Past performance is **not indicative of future results**. The creator of this indicator is **not responsible for any losses** resulting from the use of this tool. Always: * Apply proper risk management * Test strategies on demo or paper trading * Seek professional financial advice if required **You are solely responsible for your trading decisions.** --- ## 🙏 JAI SHIV SHAKTI 🙏 **Trade Smart. Trade Disciplined.**
Penunjuk Pine Script®
oleh Rajeevsharma5
AI Trend Navigator [K-Neighbor]█ Overview In the evolving landscape of trading and investment, the demand for sophisticated and reliable tools is ever-growing. The AI Trend Navigator is an indicator designed to meet this demand, providing valuable insights into market trends and potential future price movements. The AI Trend Navigator indicator is designed to predict market trends using the k-Nearest Neighbors (KNN) classifier. By intelligently analyzing recent price actions and emphasizing similar values, it helps traders to navigate complex market conditions with confidence. It provides an advanced way to analyze trends, offering potentially more accurate predictions compared to simpler trend-following methods. █ Calculations KNN Moving Average Calculation: The core of the algorithm is a KNN Moving Average that computes the mean of the 'k' closest values to a target within a specified window size. It does this by iterating through the window, calculating the absolute differences between the target and each value, and then finding the mean of the closest values. The target and value are selected based on user preferences (e.g., using the VWAP or Volatility as a target). KNN Classifier Function: This function applies the k-nearest neighbor algorithm to classify the price action into positive, negative, or neutral trends. It looks at the nearest 'k' bars, calculates the Euclidean distance between them, and categorizes them based on the relative movement. It then returns the prediction based on the highest count of positive, negative, or neutral categories. █ How to use Traders can use this indicator to identify potential trend directions in different markets. Spotting Trends: Traders can use the KNN Moving Average to identify the underlying trend of an asset. By focusing on the k closest values, this component of the indicator offers a clearer view of the trend direction, filtering out market noise. Trend Confirmation: The KNN Classifier component can confirm existing trends by predicting the future price direction. By aligning predictions with current trends, traders can gain more confidence in their trading decisions. █ Settings PriceValue: This determines the type of price input used for distance calculation in the KNN algorithm. hl2: Uses the average of the high and low prices. VWAP: Uses the Volume Weighted Average Price. VWAP: Uses the Volume Weighted Average Price. Effect: Changing this input will modify the reference values used in the KNN classification, potentially altering the predictions. TargetValue: This sets the target variable that the KNN classification will attempt to predict. Price Action: Uses the moving average of the closing price. VWAP: Uses the Volume Weighted Average Price. Volatility: Uses the Average True Range (ATR). Effect: Selecting different targets will affect what the KNN is trying to predict, altering the nature and intent of the predictions. Number of Closest Values: Defines how many closest values will be considered when calculating the mean for the KNN Moving Average. Effect: Increasing this value makes the algorithm consider more nearest neighbors, smoothing the indicator and potentially making it less reactive. Decreasing this value may make the indicator more sensitive but possibly more prone to noise. Neighbors: This sets the number of neighbors that will be considered for the KNN Classifier part of the algorithm. Effect: Adjusting the number of neighbors affects the sensitivity and smoothness of the KNN classifier. Smoothing Period: Defines the smoothing period for the moving average used in the KNN classifier. Effect: Increasing this value would make the KNN Moving Average smoother, potentially reducing noise. Decreasing it would make the indicator more reactive but possibly more prone to false signals. █ What is K-Nearest Neighbors (K-NN) algorithm? At its core, the K-NN algorithm recognizes patterns within market data and analyzes the relationships and similarities between data points. By considering the 'K' most similar instances (or neighbors) within a dataset, it predicts future price movements based on historical trends. The K-Nearest Neighbors (K-NN) algorithm is a type of instance-based or non-generalizing learning. While K-NN is considered a relatively simple machine-learning technique, it falls under the AI umbrella. We can classify the K-Nearest Neighbors (K-NN) algorithm as a form of artificial intelligence (AI), and here's why: Machine Learning Component: K-NN is a type of machine learning algorithm, and machine learning is a subset of AI. Machine learning is about building algorithms that allow computers to learn from and make predictions or decisions based on data. Since K-NN falls under this category, it is aligned with the principles of AI. Instance-Based Learning: K-NN is an instance-based learning algorithm. This means that it makes decisions based on the entire training dataset rather than deriving a discriminative function from the dataset. It looks at the 'K' most similar instances (neighbors) when making a prediction, hence adapting to new information if the dataset changes. This adaptability is a hallmark of intelligent systems. Pattern Recognition: The core of K-NN's functionality is recognizing patterns within data. It identifies relationships and similarities between data points, something akin to human pattern recognition, a key aspect of intelligence. Classification and Regression: K-NN can be used for both classification and regression tasks, two fundamental problems in machine learning and AI. The indicator code is used for trend classification, a predictive task that aligns with the goals of AI. Simplicity Doesn't Exclude AI: While K-NN is often considered a simpler algorithm compared to deep learning models, simplicity does not exclude something from being AI. Many AI systems are built on simple rules and can be combined or scaled to create complex behavior. No Explicit Model Building: Unlike traditional statistical methods, K-NN does not build an explicit model during training. Instead, it waits until a prediction is required and then looks at the 'K' nearest neighbors from the training data to make that prediction. This lazy learning approach is another aspect of machine learning, part of the broader AI field. ----------------- Disclaimer The information contained in my Scripts/Indicators/Ideas/Algos/Systems does not constitute financial advice or a solicitation to buy or sell any securities of any type. 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. My Scripts/Indicators/Ideas/Algos/Systems are only for educational purposes!
Penunjuk Pine Script®
oleh Zeiierman
49
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.
Penunjuk Pine Script®
oleh Zeiierman
3
AI Adaptive Oscillator [PhenLabs]📊 Algorithmic Adaptive Oscillator Version: PineScript™ v6 📌 Description The AI Adaptive Oscillator is a sophisticated technical indicator that employs ensemble learning and adaptive weighting techniques to analyze market conditions. This innovative oscillator combines multiple traditional technical indicators through an AI-driven approach that continuously evaluates and adjusts component weights based on historical performance. By integrating statistical modeling with machine learning principles, the indicator adapts to changing market dynamics, providing traders with a responsive and reliable tool for market analysis. 🚀 Points of Innovation: Ensemble learning framework with adaptive component weighting Performance-based scoring system using directional accuracy Dynamic volatility-adjusted smoothing mechanism Intelligent signal filtering with cooldown and magnitude requirements Signal confidence levels based on multi-factor analysis 🔧 Core Components Ensemble Framework : Combines up to five technical indicators with performance-weighted integration Adaptive Weighting : Continuous performance evaluation with automated weight adjustment Volatility-Based Smoothing : Adapts sensitivity based on current market volatility Pattern Recognition : Identifies potential reversal patterns with signal qualification criteria Dynamic Visualization : Professional color schemes with gradient intensity representation Signal Confidence : Three-tiered confidence assessment for trading signals 🔥 Key Features The indicator provides comprehensive market analysis through: Multi-Component Ensemble : Integrates RSI, CCI, Stochastic, MACD, and Volume-weighted momentum Performance Scoring : Evaluates each component based on directional prediction accuracy Adaptive Smoothing : Automatically adjusts based on market volatility Pattern Detection : Identifies potential reversal patterns in overbought/oversold conditions Signal Filtering : Prevents excessive signals through cooldown periods and minimum change requirements Confidence Assessment : Displays signal strength through intuitive confidence indicators (average, above average, excellent) 🎨 Visualization Gradient-Filled Oscillator : Color intensity reflects strength of market movement Clear Signal Markers : Distinct bullish and bearish pattern signals with confidence indicators Range Visualization : Clean representation of oscillator values from -6 to 6 Zero Line : Clear demarcation between bullish and bearish territory Customizable Colors : Color schemes that can be adjusted to match your chart style Confidence Symbols : Intuitive display of signal confidence (no symbol, +, or ++) alongside direction markers 📖 Usage Guidelines ⚙️ Settings Guide Color Settings Bullish Color Default: #2b62fa (Blue) This setting controls the color representation for bullish movements in the oscillator. The color appears when the oscillator value is positive (above zero), with intensity indicating the strength of the bullish momentum. A brighter shade indicates stronger bullish pressure. Bearish Color Default: #ce9851 (Amber) This setting determines the color representation for bearish movements in the oscillator. The color appears when the oscillator value is negative (below zero), with intensity reflecting the strength of the bearish momentum. A more saturated shade indicates stronger bearish pressure. Signal Settings Signal Cooldown (bars) Default: 10 Range: 1-50 This parameter sets the minimum number of bars that must pass before a new signal of the same type can be generated. Higher values reduce signal frequency and help prevent overtrading during choppy market conditions. Lower values increase signal sensitivity but may generate more false positives. Min Change For New Signal Default: 1.5 Range: 0.5-3.0 This setting defines the minimum required change in oscillator value between consecutive signals of the same type. It ensures that new signals represent meaningful changes in market conditions rather than minor fluctuations. Higher values produce fewer but potentially higher-quality signals, while lower values increase signal frequency. AI Core Settings Base Length Default: 14 Minimum: 2 This fundamental setting determines the primary calculation period for all technical components in the ensemble (RSI, CCI, Stochastic, etc.). It represents the lookback window for each component’s base calculation. Shorter periods create a more responsive but potentially noisier oscillator, while longer periods produce smoother signals with potential lag. Adaptive Speed Default: 0.1 Range: 0.01-0.3 Controls how quickly the oscillator adapts to new market conditions through its volatility-adjusted smoothing mechanism. Higher values make the oscillator more responsive to recent price action but potentially more erratic. Lower values create smoother transitions but may lag during rapid market changes. This parameter directly influences the indicator’s adaptiveness to market volatility. Learning Lookback Period Default: 150 Minimum: 10 Determines the historical data range used to evaluate each ensemble component’s performance and calculate adaptive weights. This setting controls how far back the AI “learns” from past performance to optimize current signals. Longer periods provide more stable weight distribution but may be slower to adapt to regime changes. Shorter periods adapt more quickly but may overreact to recent anomalies. Ensemble Size Default: 5 Range: 2-5 Specifies how many technical components to include in the ensemble calculation. Understanding The Interaction Between Settings Base Length and Learning Lookback : The base length determines the reactivity of individual components, while the lookback period determines how their weights are adjusted. These should be balanced according to your timeframe - shorter timeframes benefit from shorter base lengths, while the lookback should generally be 10-15 times the base length for optimal learning. Adaptive Speed and Signal Cooldown : These settings control sensitivity from different angles. Increasing adaptive speed makes the oscillator more responsive, while reducing signal cooldown increases signal frequency. For conservative trading, keep adaptive speed low and cooldown high; for aggressive trading, do the opposite. Ensemble Size and Min Change : Larger ensembles provide more stable signals, allowing for a lower minimum change threshold. Smaller ensembles might benefit from a higher threshold to filter out noise. Understanding Signal Confidence Levels The indicator provides three distinct confidence levels for both bullish and bearish signals: Average Confidence (▲ or ▼) : Basic signal that meets the minimum pattern and filtering criteria. These signals indicate potential reversals but with moderate confidence in the prediction. Consider using these as initial alerts that may require additional confirmation. Above Average Confidence (▲+ or ▼+) : Higher reliability signal with stronger underlying metrics. These signals demonstrate greater consensus among the ensemble components and/or stronger historical performance. They offer increased probability of successful reversals and can be traded with less additional confirmation. Excellent Confidence (▲++ or ▼++) : Highest quality signals with exceptional underlying metrics. These signals show strong agreement across oscillator components, excellent historical performance, and optimal signal strength. These represent the indicator’s highest conviction trade opportunities and can be prioritized in your trading decisions. Confidence assessment is calculated through a multi-factor analysis including: Historical performance of ensemble components Degree of agreement between different oscillator components Relative strength of the signal compared to historical thresholds ✅ Best Use Cases: Identify potential market reversals through oscillator extremes Filter trade signals based on AI-evaluated component weights Monitor changing market conditions through oscillator direction and intensity Confirm trade signals from other indicators with adaptive ensemble validation Detect early momentum shifts through pattern recognition Prioritize trading opportunities based on signal confidence levels Adjust position sizing according to signal confidence (larger for ++ signals, smaller for standard signals) ⚠️ Limitations Requires sufficient historical data for accurate performance scoring Ensemble weights may lag during dramatic market condition changes Higher ensemble sizes require more computational resources Performance evaluation quality depends on the learning lookback period length Even high confidence signals should be considered within broader market context 💡 What Makes This Unique Adaptive Intelligence : Continuously adjusts component weights based on actual performance Ensemble Methodology : Combines strength of multiple indicators while minimizing individual weaknesses Volatility-Adjusted Smoothing : Provides appropriate sensitivity across different market conditions Performance-Based Learning : Utilizes historical accuracy to improve future predictions Intelligent Signal Filtering : Reduces noise and false signals through sophisticated filtering criteria Multi-Level Confidence Assessment : Delivers nuanced signal quality information for optimized trading decisions 🔬 How It Works The indicator processes market data through five main components: Ensemble Component Calculation : Normalizes traditional indicators to consistent scale Includes RSI, CCI, Stochastic, MACD, and volume components Adapts based on the selected ensemble size Performance Evaluation : Analyzes directional accuracy of each component Calculates continuous performance scores Determines adaptive component weights Oscillator Integration : Combines weighted components into unified oscillator Applies volatility-based adaptive smoothing Scales final values to -6 to 6 range Signal Generation : Detects potential reversal patterns Applies cooldown and magnitude filters Generates clear visual markers for qualified signals Confidence Assessment : Evaluates component agreement, historical accuracy, and signal strength Classifies signals into three confidence tiers (average, above average, excellent) Displays intuitive confidence indicators (no symbol, +, ++) alongside direction markers 💡 Note: The AI Adaptive Oscillator performs optimally when used with appropriate timeframe selection and complementary indicators. Its adaptive nature makes it particularly valuable during changing market conditions, where traditional fixed-weight indicators often lose effectiveness. The ensemble approach provides a more robust analysis by leveraging the collective intelligence of multiple technical methodologies. Pay special attention to the signal confidence indicators to optimize your trading decisions - excellent (++) signals often represent the most reliable trade opportunities.
Penunjuk Pine Script®
oleh PhenLabs
1
AI Adaptive Money Flow Index (Clustering) [AlgoAlpha]🌟🚀 Dive into the future of trading with our latest innovation: the AI Adaptive Money Flow Index by AlgoAlpha Indicator! 🚀🌟 Developed with the cutting-edge power of Machine Learning, this indicator is designed to revolutionize the way you view market dynamics. 🤖💹 With its unique blend of traditional Money Flow Index (MFI) analysis and advanced k-means clustering, it adapts to market conditions like never before. Key Features: 📊 Adaptive MFI Analysis: Utilizes the classic MFI formula with a twist, adjusting its parameters based on AI-driven clustering. 🧠 AI-Driven Clustering: Applies k-means clustering to identify and adapt to market states, optimizing the MFI for current conditions. 🎨 Customizable Appearance: Offers adjustable settings for overbought, neutral, and oversold levels, as well as colors for uptrends and downtrends. 🔔 Alerts for Key Market Movements: Set alerts for trend reversals, overbought, and oversold conditions, ensuring you never miss a trading opportunity. Quick Guide to Using the AI Adaptive MFI (Clustering): 🛠 Customize the Indicator: Customize settings like MFI source, length, and k-means clustering parameters to suit your analysis. 📈 Market Analysis: Monitor the dynamically adjusted overbought, neutral, and oversold levels for insights into market conditions. Watch for classification symbols ("+", "0", "-") for immediate understanding of the current market state. Look out for reversal signals (▲, ▼) to get potential entry points. 🔔 Set Alerts: Utilize the built-in alert conditions for trend changes, overbought, and oversold signals to stay ahead, even when you're not actively monitoring the charts. How It Works: The AI Adaptive Money Flow Index employs the k-means clustering machine learning algorithm to refine the traditional Money Flow Index, dynamically adjusting overbought, neutral, and oversold levels based on market conditions. This method analyzes historical MFI values, grouping them into initial clusters using the traditional MFI's overbought, oversold and neutral levels, and then finding the mean of each cluster, which represent the new market states thresholds. This adaptive approach ensures the indicator's sensitivity in real-time, offering a nuanced understanding of market trend and volume analysis. By recalibrating MFI thresholds for each new data bar, the AI Adaptive MFI intelligently conforms to changing market dynamics. This process, assessing past periods to adjust the indicator's parameters, provides traders with insights finely tuned to recent market behavior. Such innovation enhances decision-making, leveraging the latest data to inform trading strategies. 🌐💥
Penunjuk Pine Script®
oleh AlgoAlpha
36
AI SuperTrend Clustering Oscillator [LuxAlgo]The AI SuperTrend Clustering Oscillator is an oscillator returning the most bullish/average/bearish centroids given by multiple instances of the difference between SuperTrend indicators. This script is an extension of our previously posted SuperTrend AI indicator that makes use of k-means clustering. If you want to learn more about it see: 🔶 USAGE The AI SuperTrend Clustering Oscillator is made of 3 distinct components, a bullish output (always the highest), a bearish output (always the lowest), and a "consensus" output always within the two others. The general trend is given by the consensus output, with a value above 0 indicating an uptrend and under 0 indicating a downtrend. Using a higher minimum factor will weigh results toward longer-term trends, while lowering the maximum factor will weigh results toward shorter-term trends. Strong trends are indicated when the bullish/bearish outputs are indicating an opposite sentiment. A strong bullish trend would for example be indicated when the bearish output is above 0, while a strong bearish trend would be indicated when the bullish output is below 0. When the consensus output is indicating a specific trend direction, an opposite indication from the bullish/bearish output can highlight a potential reversal or retracement. 🔶 DETAILS The indicator construction is based on finding three clusters from the difference between the closing price and various SuperTrend using different factors. The centroid of each cluster is then returned. This operation is done over all historical bars. The highest cluster will be composed of the differences between the price and SuperTrends that are the highest, thus creating a more bullish group. The lowest cluster will be composed of the differences between the price and SuperTrends that are the lowest, thus creating a more bearish group. The consensus cluster is composed of the differences between the price and SuperTrends that are not significant enough to be part of the other clusters. 🔶 SETTINGS ATR Length: ATR period used for the calculation of the SuperTrends. Factor Range: Determine the minimum and maximum factor values for the calculation of the SuperTrends. Step: Increments of the factor range. Smooth: Degree of smoothness of each output from the indicator. 🔹 Optimization This group of settings affects the runtime performances of the script. Maximum Iteration Steps: Maximum number of iterations allowed for finding centroids. Excessively low values can return a better script load time but poor clustering. Historical Bars Calculation: Calculation window of the script (in bars).
Penunjuk Pine Script®
oleh LuxAlgo
14
AI Breakout Bands (Zeiierman)█ Overview AI Breakout Bands (Zeiierman) is an adaptive trend and breakout detection system that combines Kalman filtering with advanced K-Nearest Neighbor (KNN) smoothing. The result is a smart, self-adjusting band structure that adapts to dynamic market behavior, identifying breakout conditions with precision and visual clarity. At its core, this indicator estimates price behavior using a two-dimensional Kalman filter (position + velocity), then enhances the smoothing process with a nonlinear, similarity-based KNN filter. This unique blend enables it to handle noisy markets and directional shifts with both speed and stability — providing breakout traders and trend followers a reliable framework to act on. Whether you're identifying volatility expansions, capturing trend continuations, or spotting early breakout conditions, AI Breakout Bands gives you a mathematically grounded, visually adaptive roadmap of real-time market structure. █ How It Works ⚪ Kalman Filter Engine The Kalman filter models price movement as a state system with two components: Position (price) Velocity (trend direction) It recursively updates predictions using real-time price as a noisy observation, balancing responsiveness with smoothness. Process Noise (Position) controls sensitivity to sudden moves. Process Noise (Velocity) controls smoothing of directional flow. Measurement Noise (R) defines how much the filter "trusts" live price data. This component alone creates a responsive yet stable estimate of the market’s center of gravity. ⚪ Advanced K-Neighbor Smoothing After the Kalman estimate is computed, the script applies a custom K-Nearest Neighbor (KNN) smoother. Rather than averaging raw values, this method: Finds K most similar past Kalman values Weighs them by similarity (inverse of absolute distance) Produces a smoother that emphasizes structural similarity This nonlinear approach gives the indicator an AI feature — reacting fast when needed, yet staying calm in consolidation. █ How to Use ⚪ Trend Recognition The line color shifts dynamically based on slope direction and breakout confirmation. Bullish conditions: price above the mid band with positive slope Bearish conditions: price below the mid band with negative slope ⚪ Breakout Signals Price breaking above or below the bands may signal momentum acceleration. Combine with your own volume or momentum confirmation for stronger entries. Bands adapt to market noise, helping filter out low-quality whipsaws. █ Settings Process Noise (Position): Controls Kalman filter’s sensitivity to price changes. Process Noise (Velocity): Controls smoothing of directional component. Measurement Noise (R): Defines how much trust is placed in price data. K-Neighbor Length: Number of historical Kalman values considered for smoothing. Slope Calculation Window: Number of bars used to compute trend slope of the smoothed Kalman. Band Lookback (MAE): Rolling period for average absolute error. Band Multiplier: Multiplies MAE to determine band width. ----------------- 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.
Penunjuk Pine Script®
oleh Zeiierman
8
AI Volume Breakout for scalpingPurpose of the Indicator This script is designed for trading, specifically for scalping, which involves making numerous trades within a very short time frame to take advantage of small price movements. The indicator looks for volume breakouts, which are moments when trading volume significantly increases, potentially signaling the start of a new price movement. Key Components: Parameters: Volume Threshold (volumeThreshold): Determines how much volume must increase from one bar to the next for it to be considered significant. Set at 4.0, meaning volume must quadruplicate for a breakout signal. Price Change Threshold (priceChangeThreshold): Defines the minimum price change required for a breakout signal. Here, it's 1.5% of the bar's opening price. SMA Length (smaLength): The period for the Simple Moving Average, which helps confirm the trend direction. Here, it's set to 20. Cooldown Period (cooldownPeriod): Prevents signals from being too close together, set to 10 bars. ATR Period (atrPeriod): The period for calculating Average True Range (ATR), used to measure market volatility. Volatility Threshold (volatilityThreshold): If ATR divided by the close price exceeds this, the market is considered too volatile for trading according to this strategy. Calculations: SMA (Simple Moving Average): Used for trend confirmation. A bullish signal is more likely if the price is above this average. ATR (Average True Range): Measures market volatility. Lower volatility (below the threshold) is preferred for this strategy. Signal Generation: The indicator checks if: Volume has increased significantly (volumeDelta > 0 and volume / volume >= volumeThreshold). There's enough price change (math.abs(priceDelta / open) >= priceChangeThreshold). The market isn't too volatile (lowVolatility). The trend supports the direction of the price change (trendUp for bullish, trendDown for bearish). If all these conditions are met, it predicts: 1 (Bullish) if conditions suggest buying. 0 (Bearish) if conditions suggest selling. Cooldown Mechanism: After a signal, the script waits for a number of bars (cooldownPeriod) before considering another signal to avoid over-trading. Visual Feedback: Labels are placed on the chart: Green label for bullish breakouts below the low price. Red label for bearish breakouts above the high price. How to Use: Entry Points: Look for the labels on your chart to decide when to enter trades. Risk Management: Since this is for scalping, ensure each trade has tight stop-losses to manage risk due to the quick, small movements. Market Conditions: This strategy might work best in markets with consistent volume and price changes but not extreme volatility. Caveats: This isn't real AI; it's a heuristic based on volume and price. Actual AI would involve machine learning algorithms trained on historical data. Always backtest any strategy, and consider how it behaves in different market conditions, not just the ones it was designed for.
Penunjuk Pine Script®
oleh Trading_Indicator_Pro
18
AI Channels (Clustering) [LuxAlgo]The AI Channels indicator is constructed based on rolling K-means clustering, a common machine learning method used for clustering analysis. These channels allow users to determine the direction of the underlying trends in the price. We also included an option to display the indicator as a trailing stop from within the settings. 🔶 USAGE Each channel extremity allows users to determine the current trend direction. Price breaking over the upper extremity suggesting an uptrend, and price breaking below the lower extremity suggesting a downtrend. Using a higher Window Size value will return longer-term indications. The "Clusters" setting allows users to control how easy it is for the price to break an extremity, with higher values returning extremities further away from the price. The "Denoise Channels" is enabled by default and allows to see less noisy extremities that are more coherent with the detected trend. Users who wish to have more focus on a detected trend can display the indicator as a trailing stop. 🔹 Centroid Dispersion Areas Each extremity is made of one area. The width of each area indicates how spread values within a cluster are around their centroids. A wider area would suggest that prices within a cluster are more spread out around their centroid, as such one could say that it is indicative of the volatility of a cluster. Wider areas around a specific extremity can indicate a larger and more spread-out amount of prices within the associated cluster. In practice price entering an area has a higher chance to break an associated extremity. 🔶 DETAILS The indicator performs K-means clustering over the most recent Window Size prices, finding a number of user-specified clusters. See here to find more information on cluster detection. The channel extremities are returned as the centroid of the lowest, average, and highest price clusters. K-means clustering can be computationally expensive and as such we allow users to determine the maximum number of iterations used to find the centroids as well as the number of most historical bars to perform the indicator calculation. Do note that increasing the calculation window of the indicator as well as the number of clusters will return slower results. 🔶 SETTINGS Window Size: Amount of most recent prices to use for the calculation of the indicator. Clusters": Amount of clusters detected for the calculation of the indicator. Denoise Channels: When enabled, return less noisy channels extremities, disabling this setting will return the exact centroids at each time but will produce less regular extremities. As Trailing Stop: Display the indicator as a trailing stop. 🔹 Optimization This group of settings affects the runtime performance of the script. Maximum Iteration Steps: Maximum number of iterations allowed for finding centroids. Excessively low values can return a better script load time but poor clustering. Historical Bars Calculation: Calculation window of the script (in bars).
Penunjuk Pine Script®
oleh LuxAlgo
16
AI Sniper ToolOverview The AI Sniper Tool is a visual trend, volatility, and risk-context indicator designed to help structure market behavior using dynamic price bands and a zero-lag trend filter. It combines statistical price bands, trend-state evaluation, and position-size reference visualization to support structured market analysis. The indicator is not an automated trading system and is intended purely as an analytical aid. How it works The indicator calculates multi-layered upper and lower price bands based on a moving average and standard deviation, providing a visual representation of volatility expansion and price extremes. A zero-lag EMA-based trend filter evaluates price behavior relative to adaptive volatility thresholds. Trend states are internally classified and updated when price crosses defined boundaries. Trend & context logic Trend states are interpreted as directional context, not as predictions. Visual markers appear only when the internal trend state changes, highlighting potential market phase transitions. These visual elements are not trade recommendations, but graphical references for contextual awareness. Risk visualization An integrated risk reference module calculates a theoretical position size based on: a user-defined account balance a fixed percentage risk assumption a price-dependent distance reference All calculated values are informational only and do not constitute trading advice. Visualization Multi-layer volatility bands with gradient fills Central mean line for structural reference Visual trend-state markers on transitions Informative labels displaying risk-based reference values All elements are intended purely for visual and analytical purposes. Alerts Optional alerts notify users of trend-state changes and provide contextual reference information only. Alerts are designed for monitoring purposes and do not represent automated trade signals. Intended use This tool supports: Trend and volatility analysis Market phase identification Risk and position-size reference visualization It should be used in conjunction with independent analysis and proper risk management. Notes This indicator: does not predict price direction does not provide trade or entry signals is intended purely as a visual analytical reference tool
Penunjuk Pine Script®
oleh Seboo88
AI Session KillzoneOverview The AI Session indicator visualizes the Asian, London, and New York trading sessions directly on the chart and dynamically tracks each session’s high, low, and midpoint. This indicator is designed as a session structure and liquidity context tool and does not generate trade, entry, or exit signals. How it works The indicator uses a DST-aware New York timezone to ensure accurate session alignment throughout the year. Each trading session is defined via customizable session inputs and highlighted using color-coded backgrounds. During an active session, the indicator continuously updates: the session high the session low and the session midpoint These levels are plotted as horizontal reference lines and extended forward in time to observe future price interaction. Session interaction logic The indicator monitors when price touches or trades through highs or lows from previous sessions, including: Asia session levels during the London session Asia and London session levels during the New York session Once a session level is touched, it is locked to prevent repeated events. All interactions are visually marked directly on the chart. Visualization Color-coded session backgrounds Horizontal lines for session highs, lows, and midpoints Dashed markers indicating session starts All elements are intended purely as visual reference tools and update dynamically with price. Alerts Optional alerts are triggered when: Asia High or Low is touched during the London session Asia High or Low is touched during the New York session London High or Low is touched during the New York session Alerts trigger only once per level to avoid duplicate notifications. Intended use This tool supports: Session-based market analysis Liquidity mapping Time-of-day and session context for intraday trading It should be used in combination with broader market context and risk management. Notes This indicator: does not predict price direction does not provide trade or entry signals is intended purely as a visual and analytical reference
Penunjuk Pine Script®
oleh Seboo88
AI LiquidityOverview The AI Liquidity indicator identifies and visualizes key liquidity highs and lows derived from a higher timeframe (HTF) and projects them as horizontal reference levels onto the active chart. Its primary purpose is to observe liquidity interactions, especially when price touches or trades through existing high or low levels. The indicator is designed as a liquidity and market-structure reference tool and does not generate trade, entry, or exit signals. How it works The indicator aggregates candles from a selected higher timeframe (HTF) and evaluates consecutive HTF candles to determine structurally relevant highs and lows. These liquidity levels are: plotted as horizontal lines extended forward in time accompanied by dynamic labels showing how long the level has been active Optional visual references of the originating HTF candles can be displayed to provide additional structural context. Liquidity sweep logic The indicator monitors when price touches or trades through an active liquidity level. When this occurs, the level is classified as a liquidity sweep and its visual state is updated accordingly (e.g. dashed styling and markers). Swept levels are automatically removed after a defined number of bars to keep the chart clean and focused on relevant structures. Session filter Liquidity interactions and background highlights can be restricted to a predefined trading session, ensuring that visual emphasis and alerts are only active during the intended time window. Visualization Horizontal lines for liquidity highs and lows Dynamic labels indicating time since level creation Dashed styling after liquidity interaction Optional HTF reference candle visualization Subtle background highlighting following the most recent liquidity event All elements are intended purely as visual and analytical references. Alerts Optional alerts may trigger when: a liquidity high is swept a liquidity low is swept Alerts are designed to trigger in a controlled manner to avoid duplicate notifications. Intended use This tool supports: Liquidity-based market analysis Higher-timeframe structure evaluation Intraday and swing context when combined with broader market analysis It should be used alongside proper risk management and additional confirmation tools. Notes This indicator: does not predict price direction does not provide trade or entry signals is intended purely as a visual and analytical reference tool
Penunjuk Pine Script®
oleh Seboo88
AI Demand Strategy (Long Only) professionals.aiThe "AI Demand Strategy (Long Only) professionals.ai" is a TradingView strategy designed for USDT-based spot trading. It focuses on long-only entries, incorporates optional trend filtering, and includes configurable risk-to-reward settings for exit targets. It provides: Customizable parameters for sensitivity, risk/reward ratio, and trend filtering Automated entry and exit management Stop-loss and take-profit level plotting on the chart Visual buy/sell markers for trade signals Optional SMA filter for trend confirmation Built-in alert conditions to connect with external trading automation systems This setup allows traders to visually monitor trade levels, backtest performance, and automate alerts without manually tracking market conditions.
Strategi Pine Script®
oleh professionals-ai
AI Momentum [YinYang]Overview: AI Momentum is a kernel function based momentum Indicator. It uses Rational Quadratics to help smooth out the Moving Averages, this may give them a more accurate result. This Indicator has 2 main uses, first it displays ‘Zones’ that help you visualize the potential movement areas and when the price is out of bounds (Overvalued or Undervalued). Secondly it creates signals that display the momentum of the current trend. The Zones are composed of the Highest Highs and Lowest lows turned into a Rational Quadratic over varying lengths. These create our Rational High and Low zones. There is however a second zone. The second zone is composed of the avg of the Inner High and Inner Low zones (yellow line) and the Rational Quadratic of the current Close. This helps to create a second zone that is within the High and Low bounds that may represent momentum changes within these zones. When the Rationalized Close crosses above the High and Low Zone Average it may signify a bullish momentum change and vice versa when it crosses below. There are 3 different signals created to display momentum: Bullish and Bearish Momentum. These signals display when there is current bullish or bearish momentum happening within the trend. When the momentum changes there will likely be a lull where there are neither Bullish or Bearish momentum signals. These signals may be useful to help visualize when the momentum has started and stopped for both the bulls and the bears. Bullish Momentum is calculated by checking if the Rational Quadratic Close > Rational Quadratic of the Highest OHLC4 smoothed over a VWMA. The Bearish Momentum is calculated by checking the opposite. Overly Bullish and Bearish Momentum. These signals occur when the bar has Bullish or Bearish Momentum and also has an Rationalized RSI greater or less than a certain level. Bullish is >= 57 and Bearish is <= 43. There is also the option to ‘Factor Volume’ into these signals. This means, the Overly Bullish and Bearish Signals will only occur when the Rationalized Volume > VWMA Rationalized Volume as well as the previously mentioned factors above. This can be useful for removing ‘clutter’ as volume may dictate when these momentum changes will occur, but it can also remove some of the useful signals and you may miss the swing too if the volume just was low. Overly Bullish and Bearish Momentum may dictate when a momentum change will occur. Remember, they are OVERLY Bullish and Bearish, meaning there is a chance a correction may occur around these signals. Bull and Bear Crosses. These signals occur when the Rationalized Close crosses the Gaussian Close that is 2 bars back. These signals may show when there is a strong change in momentum, but be careful as more often than not they’re predicting that the momentum may change in the opposite direction. Tutorial: As we can see in the example above, generally what happens is we get the regular Bullish or Bearish momentum, followed by the Rationalized Close crossing the Zone average and finally the Overly Bullish or Bearish signals. This is normally the order of operations but isn’t always how it happens as sometimes momentum changes don’t make it that far; also the Rationalized Close and Zone Average don’t follow any of the same math as the Signals which can result in differing appearances. The Bull and Bear Crosses are also quite sporadic in appearance and don’t generally follow any sort of order of operations. However, they may occur as a Predictor between Bullish and Bearish momentum, signifying the beginning of the momentum change. The Bull and Bear crosses may be a Predictor of momentum change. They generally happen when there is no Bullish or Bearish momentum happening; and this helps to add strength to their prediction. When they occur during momentum (orange circle) there is a less likely chance that it will happen, and may instead signify the exact opposite; it may help predict a large spike in momentum in the direction of the Bullish or Bearish momentum. In the case of the orange circle, there is currently Bearish Momentum and therefore the Bull Cross may help predict a large momentum movement is about to occur in favor of the Bears. We have disabled signals here to properly display and talk about the zones. As you can see, Rationalizing the Highest Highs and Lowest Lows over 2 different lengths creates inner and outer bounds that help to predict where parabolic movement and momentum may move to. Our Inner and Outer zones are great for seeing potential Support and Resistance locations. The secondary zone, which can cross over and change from Green to Red is also a very important zone. Let's zoom in and talk about it specifically. The Middle Zone Crosses may help deduce where parabolic movement and strong momentum changes may occur. Generally what may happen is when the cross occurs, you will see parabolic movement to the High / Low zones. This may be the Inner zone but can sometimes be the outer zone too. The hard part is sometimes it can be a Fakeout, like displayed with the Blue Circle. The Cross doesn’t mean it may move to the opposing side, sometimes it may just be predicting Parabolic movement in a general sense. When we turn the Momentum Signals back on, we can see where the Fakeout occurred that it not only almost hit the Inner Low Zone but it also exhibited 2 Overly Bearish Signals. Remember, Overly bearish signals mean a momentum change in favor of the Bulls may occur soon and overly Bullish signals mean a momentum change in favor of the Bears may occur soon. You may be wondering, well what does “may occur soon” mean and how do we tell? The purpose of the momentum signals is not only to let you know when Momentum has occurred and when it is still prevalent. It also matters A LOT when it has STOPPED! In this example above, we look at when the Overly Bullish and Bearish Momentum has STOPPED. As you can see, when the Overly Bullish or Bearish Momentum stopped may be a strong predictor of potential momentum change in the opposing direction. We will conclude our Tutorial here, hopefully this Indicator has been helpful for showing you where momentum is occurring and help predict how far it may move. We have been dabbling with and are planning on releasing a Strategy based on this Indicator shortly. Settings: 1. Momentum: Show Signals: Sometimes it can be difficult to visualize the zones with signals enabled. Factor Volume: Factor Volume only applies to Overly Bullish and Bearish Signals. It's when the Volume is > VWMA Volume over the Smoothing Length. Zone Inside Length: The Zone Inside is the Inner zone of the High and Low. This is the length used to create it. Zone Outside Length: The Zone Outside is the Outer zone of the High and Low. This is the length used to create it. Smoothing length: Smoothing length is the length used to smooth out our Bullish and Bearish signals, along with our Overly Bullish and Overly Bearish Signals. 2. Kernel Settings: Lookback Window: The number of bars used for the estimation. This is a sliding value that represents the most recent historical bars. Recommended range: 3-50. Relative Weighting: Relative weighting of time frames. As this value approaches zero, the longer time frames will exert more influence on the estimation. As this value approaches infinity, the behavior of the Rational Quadratic Kernel will become identical to the Gaussian kernel. Recommended range: 0.25-25. Start Regression at Bar: Bar index on which to start regression. The first bars of a chart are often highly volatile, and omission of these initial bars often leads to a better overall fit. Recommended range: 5-25. If you have any questions, comments, ideas or concerns please don't hesitate to contact us. HAPPY TRADING!
Penunjuk Pine Script®
oleh YinYangAlgorithms
9
AI-JX# AI-JX v3.0 指标技术分析文档 / Technical Analysis Documentation ## 1. 指标概述 / Indicator Overview AI-JX v3.0 是一个集成了人工智能学习系统的高级技术分析指标，结合了传统技术指标与AI预测功能，提供多维度的市场分析和交易信号。该指标基于Heikin Ashi蜡烛图和SuperTrend技术，通过AI权重学习系统动态优化参数组合。 AI-JX v3.0 is an advanced technical analysis indicator that integrates an artificial intelligence learning system, combining traditional technical indicators with AI prediction capabilities to provide multi-dimensional market analysis and trading signals. The indicator is based on Heikin Ashi candlesticks and SuperTrend technology, dynamically optimizing parameter combinations through an AI weight learning system. ## 2. 核心信号系统 / Core Signal System ### 2.1 主要交易信号 / Main Trading Signals #### AI智能买卖信号 / AI Smart Buy/Sell Signals - **AI买入信号 / AI Buy Signal**: 当buyScore ≥ 70分且AI确认无假突破时触发 / Triggered when buyScore ≥ 70 and AI confirms no false breakout - **AI卖出信号 / AI Sell Signal**: 当sellScore ≥ 70分且AI确认无假突破时触发 / Triggered when sellScore ≥ 70 and AI confirms no false breakout - **信号特点 / Signal Features**: 基于多指标融合评分，具有较高的准确性 / Based on multi-indicator fusion scoring with high accuracy #### 传统SuperTrend信号 / Traditional SuperTrend Signals - **传统买入 / Traditional Buy**: 趋势从下降转为上升时触发 / Triggered when trend changes from down to up - **传统卖出 / Traditional Sell**: 趋势从上升转为下降时触发 / Triggered when trend changes from up to down - **显示方式 / Display Method**: 小尺寸标签，作为参考信号 / Small-sized labels as reference signals ### 2.2 预测性信号 / Predictive Signals #### 预测强买信号 / Predictive Strong Buy Signal **触发条件 / Trigger Conditions**: - RSI < 35 (超卖 / Oversold) - MACD线上穿信号线 / MACD line crosses above signal line - 价格接近支撑位(距离<2.5%) / Price near support level (distance <2.5%) - 成交量放大确认(>1.5倍均量) / Volume confirmation (>1.5x average volume) - 无假突破向下 / No false breakout downward #### 预测强空信号 / Predictive Strong Sell Signal **触发条件 / Trigger Conditions**: - RSI > 65 (超买 / Overbought) - MACD线下穿信号线 / MACD line crosses below signal line - 价格接近阻力位(距离<2.5%) / Price near resistance level (distance <2.5%) - 成交量放大确认(>1.5倍均量) / Volume confirmation (>1.5x average volume) - 无假突破向上 / No false breakout upward ### 2.3 背离信号 / Divergence Signals #### 预测性看涨背离 / Predictive Bullish Divergence - 价格创新低但RSI未创新低 / Price makes new low but RSI doesn't make new low - 结合成交量和动量确认 / Combined with volume and momentum confirmation - 提示潜在的反转机会 / Indicates potential reversal opportunity #### 预测性看跌背离 / Predictive Bearish Divergence - 价格创新高但RSI未创新高 / Price makes new high but RSI doesn't make new high - 结合成交量和动量确认 / Combined with volume and momentum confirmation - 提示潜在的顶部风险 / Indicates potential top risk ## 3. AI学习系统 / AI Learning System ### 3.1 参数组合策略 / Parameter Combination Strategies #### 保守型组合 / Conservative Combination - **适用场景 / Application Scenario**: 横盘震荡市场 / Sideways oscillating markets - **RSI周期 / RSI Period**: 21 - **MACD参数 / MACD Parameters**: 12,26,9 - **ATR周期 / ATR Period**: 14 - **特点 / Features**: 稳定性高，信号较少但准确性好 / High stability, fewer signals but good accuracy #### 激进型组合 / Aggressive Combination - **适用场景 / Application Scenario**: 强趋势突破市场 / Strong trending breakout markets - **RSI周期 / RSI Period**: 12 - **MACD参数 / MACD Parameters**: 6,21,5 - **ATR周期 / ATR Period**: 10 - **特点 / Features**: 敏感性高，信号较多但需要过滤 / High sensitivity, more signals but require filtering #### 平衡型组合 / Balanced Combination - **适用场景 / Application Scenario**: 通用市场环境 / General market conditions - **RSI周期 / RSI Period**: 17 - **MACD参数 / MACD Parameters**: 10,24,7 - **ATR周期 / ATR Period**: 12 - **特点 / Features**: 平衡敏感性和稳定性 / Balances sensitivity and stability ### 3.2 权重自适应调整 / Adaptive Weight Adjustment - **学习机制 / Learning Mechanism**: 基于历史交易表现动态调整权重 / Dynamically adjusts weights based on historical trading performance - **最小学习交易数 / Minimum Learning Trades**: 20笔 / 20 trades - **学习速率 / Learning Rate**: 0.1 (可调 / adjustable) - **记忆长度 / Memory Length**: 100笔交易 / 100 trades ## 4. 市场状态识别 / Market State Recognition ### 4.1 市场模式分类 / Market Pattern Classification - **强趋势突破 / Strong Trend Breakout**: 波动率>1.5且趋势强度>5% / Volatility >1.5 and trend strength >5% - **横盘震荡 / Sideways Oscillation**: 波动率<0.7且趋势强度<2% / Volatility <0.7 and trend strength <2% - **上升趋势 / Uptrend**: 20日涨幅>3% / 20-day gain >3% - **下降趋势 / Downtrend**: 20日跌幅>3% / 20-day decline >3% - **弱势整理 / Weak Consolidation**: 其他情况 / Other conditions ### 4.2 支撑阻力分析 / Support and Resistance Analysis #### 动态支撑阻力 / Dynamic Support and Resistance - **计算方式 / Calculation Method**: 基于历史高低点统计 / Based on historical high/low statistics - **强度分级 / Strength Classification**: 强/中等/弱 (基于触及次数) / Strong/Medium/Weak (based on touch count) - **有效性 / Validity**: 价格偏差<0.2%认定为有效触及 / Price deviation <0.2% considered valid touch #### 斐波那契关键位 / Fibonacci Key Levels - **23.6%回撤位 / 23.6% Retracement** - **38.2%回撤位 / 38.2% Retracement** - **50.0%回撤位 / 50.0% Retracement** - **61.8%回撤位 / 61.8% Retracement** - **78.6%回撤位 / 78.6% Retracement** ## 5. 风险控制机制 / Risk Control Mechanisms ### 5.1 假突破识别 / False Breakout Identification #### 向上假突破 / Upward False Breakout - 价格突破阻力位后快速回落 / Price breaks resistance then quickly falls back - 成交量萎缩(<0.8倍均量) / Volume shrinks (<0.8x average volume) - 自动过滤相关买入信号 / Automatically filters related buy signals #### 向下假突破 / Downward False Breakout - 价格跌破支撑位后快速反弹 / Price breaks support then quickly rebounds - 成交量萎缩(<0.8倍均量) / Volume shrinks (<0.8x average volume) - 自动过滤相关卖出信号 / Automatically filters related sell signals ### 5.2 多时间框架验证 / Multi-Timeframe Validation - **时间框架1 / Timeframe 1**: 5分钟 / 5 minutes - **时间框架2 / Timeframe 2**: 15分钟 / 15 minutes - **时间框架3 / Timeframe 3**: 60分钟 / 60 minutes - **一致性要求 / Consistency Requirement**: 三个时间框架趋势方向一致时信号更可靠 / Signals are more reliable when all three timeframes show consistent trend direction ## 6. AI预测功能 / AI Prediction Features ### 6.1 趋势预测系统 / Trend Prediction System #### 预测评分机制 / Prediction Scoring Mechanism - **多时间框架一致性 / Multi-Timeframe Consistency**: 30分 / 30 points - **价格动量分析 / Price Momentum Analysis**: 25分 / 25 points - **成交量确认 / Volume Confirmation**: 20分 / 20 points - **支撑阻力位置 / Support/Resistance Position**: 25分 / 25 points #### 预测结果分类 / Prediction Result Classification - **强烈看涨 / Strong Bullish**: 评分>80 / Score >80 - **温和看涨 / Moderate Bullish**: 评分60-80 / Score 60-80 - **震荡 / Sideways**: 评分40-60 / Score 40-60 - **温和看跌 / Moderate Bearish**: 评分20-40 / Score 20-40 - **强烈看跌 / Strong Bearish**: 评分<20 / Score <20 ### 6.2 智能点位识别 / Smart Level Identification #### 最佳做多点位 / Optimal Long Entry Points - 基于支撑位和斐波那契回撤 / Based on support levels and Fibonacci retracements - 结合RSI超卖和MACD金叉 / Combined with RSI oversold and MACD golden cross - 提供具体价位和置信度 / Provides specific price levels and confidence scores #### 最佳做空点位 / Optimal Short Entry Points - 基于阻力位和斐波那契回撤 / Based on resistance levels and Fibonacci retracements - 结合RSI超买和MACD死叉 / Combined with RSI overbought and MACD death cross - 提供具体价位和置信度 / Provides specific price levels and confidence scores ## 7. 使用建议 / Usage Recommendations ### 7.1 信号优先级 / Signal Priority 1. **最高优先级 / Highest Priority**: AI智能信号(评分≥70) / AI smart signals (score ≥70) 2. **高优先级 / High Priority**: 预测性信号+多时间框架确认 / Predictive signals + multi-timeframe confirmation 3. **中等优先级 / Medium Priority**: 传统SuperTrend信号 / Traditional SuperTrend signals 4. **参考级别 / Reference Level**: 背离信号和支撑阻力提示 / Divergence signals and support/resistance hints ### 7.2 参数设置建议 / Parameter Setting Recommendations #### 新手用户 / Beginner Users - 启用AI学习系统 / Enable AI learning system - 使用平衡型组合 / Use balanced combination - 关注预测性信号 / Focus on predictive signals - 重视风险控制 / Emphasize risk control #### 经验用户 / Experienced Users - 根据市场环境选择组合 / Choose combinations based on market conditions - 结合多时间框架分析 / Combine multi-timeframe analysis - 自定义学习参数 / Customize learning parameters - 灵活运用各类信号 / Flexibly use various signal types ### 7.3 风险提示 / Risk Warnings - **AI学习需要时间 / AI Learning Takes Time**: 至少20笔交易后才开始有效学习 / Effective learning starts after at least 20 trades - **市场环境变化 / Market Environment Changes**: 需要定期重新训练AI系统 / AI system needs periodic retraining - **信号延迟 / Signal Delay**: 部分信号可能存在1-2根K线的延迟 / Some signals may have 1-2 candlestick delay - **假信号风险 / False Signal Risk**: 震荡市场中可能产生较多假信号 / May generate more false signals in choppy markets - **过度优化 / Over-optimization**: 避免频繁调整参数导致过拟合 / Avoid frequent parameter adjustments causing overfitting ## 8. 显示面板说明 / Display Panel Description ### 8.1 AI统计面板 / AI Statistics Panel 显示内容包括 / Display contents include: - 风险等级和买卖评分 / Risk level and buy/sell scores - 市场状态和波动率 / Market state and volatility - RSI当前值 / Current RSI value - AI趋势预测和置信度 / AI trend prediction and confidence - 最佳入场点位 / Optimal entry points - 交易机会评估 / Trading opportunity assessment - AI准确率统计 / AI accuracy statistics ### 8.2 AI预测信息面板 / AI Prediction Information Panel 显示内容包括 / Display contents include: - 趋势方向和置信度 / Trend direction and confidence - 价格目标位 / Price target levels - 最佳做多/做空点位 / Optimal long/short entry points - 交易机会类型 / Trading opportunity type - 入场时机建议 / Entry timing recommendations - 市场情绪分析 / Market sentiment analysis - 价格形态识别 / Price pattern recognition ## 9. 总结 / Summary AI-JX v3.0指标通过集成多种技术分析方法和AI学习能力，为交易者提供了一个全面的市场分析工具。其核心优势在于: The AI-JX v3.0 indicator provides traders with a comprehensive market analysis tool by integrating various technical analysis methods and AI learning capabilities. Its core advantages include: - **智能化 / Intelligence**: AI自动学习和优化参数 / AI automatically learns and optimizes parameters - **多维度 / Multi-dimensional**: 结合趋势、动量、支撑阻力等多个维度 / Combines trend, momentum, support/resistance and other dimensions - **预测性 / Predictive**: 提供前瞻性的市场预测 / Provides forward-looking market predictions - **风险控制 / Risk Control**: 内置假突破识别和多重确认机制 / Built-in false breakout identification and multiple confirmation mechanisms 建议交易者在使用时结合自身交易风格和市场环境，合理设置参数，并注意风险管理。 It is recommended that traders combine their own trading style and market environment when using this indicator, set parameters reasonably, and pay attention to risk management.
Penunjuk Pine Script®
oleh shaw_gao
5
Kioseff Trading - AI-Optimized Supertrend AI-Optimized Supertrend Introducing AI-Optimized Supertrend: a streamlined solution for traders of any skill level seeking to rapidly test and optimize Supertrend. Capable of analyzing thousands of strategies, this tool cuts through the complexity to identify the most profitable, reliable, or efficient approaches. Paired with TradingView's native backtesting capabilities, the AI-Optimized Supertrend learns from historical performance data. Set up is easy for all skill levels, and it makes fine-tuning trading alerts and Supertrend straightforward. Features Rapid Supertrend Strategy Testing : Quickly evaluate thousands of Supertrend strategies to find the most effective ones. AI-Assisted Optimization : Leverage AI recommendations to fine-tune strategies for superior results. Multi-Objective Optimization : Prioritize Supertrend based on your preference for the highest win rate, maximum profit, or efficiency. Comprehensive Analytics : The strategy script provides an array of statistics such as profit factor, PnL, win rate, trade counts, max drawdown, and an equity curve to gauge performance accurately. Alerts Setup : Conveniently set up alerts to be notified about critical trade signals or changes in performance metrics. Versatile Stop Strategies : Experiment with profit targets, trailing stops, and fixed stop losses. Binary Supertrend Exploration : Test binary Supertrend strategies. Limit Orders : Analyze the impact of limit orders on your trading strategy. Integration with External Indicators : Enhance strategy refinement by incorporating custom or publicly available indicators from TradingView into the optimization process. Key Settings The image above shows explanations for a list of key settings for the optimizer. Set the Factor Range Limits : The AI suggests optimal upper and lower limits for the Factor range, defining the sensitivity of the Supertrend to price fluctuations. A wider range tests a greater variety, while a narrower range focuses on fine-tuning. Adjust the ATR Range : Use the AI's recommendations to establish the upper and lower bounds for the Average True Range (ATR), which influences the Supertrend's volatility threshold. ATR Flip : This option lets you interchange the order of ATR and Factor values to quicky test different sequences, giving you the flexibility to explore various combinations and their impact on the Supertrend indicator's performance. Strategies Evaluated : Adjust this setting to determine how many Supertrend strategies you want to assess and compare. Enable AI Mode : Turn this feature on to allow the AI to determine and employ the optimal Supertrend strategy with the desired performance metric, such as the highest win rate or maximum profitability. Target Metric : Adjust this to direct the AI towards optimizing for maximum profit, top win rates, or the most efficient profits. AI Mode Aggressiveness : Set how assertively the AI pursues the chosen performance goal, such as highest profit or win rate. Strategy Direction : Choose to focus the AI's testing and optimization on either long or short Supertrend strategies. Stop Loss Type : Specify the stop loss approach for optimization—fixed value, a trailing stop, or Supertrend direction changes. Limit Order : Decide if you want to execute trades using limit orders for setting your profit targets, stop losses, or apply them to both. Profit Target : Define your desired profit level when using either a fixed stop loss or a trailing stop. Stop Loss : Define your desired stop loss when using either a fixed stop loss or a trailing stop. How to: Find the best Supertrend for trading It's important to remember that merely having the AI-Optimized Supertrend on your chart doesn't automatically provide you with the best strategy. You need to follow the AI's guidance through an iterative process to discover the optimal Supertrend settings and strategy. Optimizing Supertrend involves adjusting two key parameters: the Factor and the Average True Range (ATR). These parameters significantly influence the Supertrend indicator's sensitivity and responsiveness to price movements. Factor : This parameter multiplies the ATR to determine the distance of the Supertrend line from the price. Higher values will create a wider band, potentially leading to fewer trade signals, while lower values create a narrower band, which may result in more signals but also more noise. ATR (Average True Range) : ATR measures market volatility. By using the ATR, the Supertrend adapts to changing market volatility; a higher ATR value means a more volatile market, so the Supertrend adjusts accordingly. During the optimization process, these parameters are systematically varied to determine the combination that yields the best performance based on predefined criteria such as profitability, win rate, or risk management efficiency. The optimization aims to find the optimal Factor and ATR settings. 1.Starting Your Strategy Setup Begin by deciding your goals for each trade: your profit target and stop loss, or if all trades exit when Supertrend changes direction. You'll also choose how to manage your stops – whether they stay put (fixed) or move with the price (trailing), and whether you want to exit trades at a specific price (limit orders). Keep the initial settings for Supertrend Factor Range and Supertrend ATR Range at their default to give the tool a broad testing field. The AI's guidance will refine these settings to pinpoint the most effective ones through a process of comprehensive testing. Demonstration Start: We'll begin with the settings outlined in the key settings section, using Supertrend's direction change to the downside as our exit signal for all trades. 2. Continue applying the AI’s suggestions Keep updating your optimization settings based on the AI's recommendations. Proceed with this iterative optimization until the "Best Found" message is displayed, signaling that the most effective strategy has been identified. While following the AI's suggestions, we've been prompted with a new suggestion: increase the number of strategies evaluated. Keep following the AI's new suggestions to evaluate more strategies. Do this until the "Best Found" message shows up. Success! We continued to follow the AI’s suggestions until “Best Found” was indicated! AI Mode AI Mode incorporates Heuristic-Based Adaptive Learning to fine-tune trading strategies in a continuous manner. This feature consists of two main components: Heuristic-Based Decision Making: The algorithm evaluates multiple Supertrend-based trading strategies using metrics such as Profit and Loss (PNL), Win Rate, and Most Efficient Profit. These metrics act as heuristics to assist the algorithm in identifying suitable strategies for trade execution. Online Learning: The algorithm updates the performance evaluations of each strategy based on incoming market data. This enables the system to adapt to current market conditions. Incorporating both heuristic-based decision-making and online learning, this feature aims to provide a framework for trading strategy optimization. AI Mode Settings AI Mode Aggressiveness: Description: The "AI Mode Aggressiveness" setting allows you to fine-tune the AI's trading behavior. This setting ranges from “Low” to “High”, with “High” indicating a more assertive trading approach. Functionality: This feature filters trading strategies based on a proprietary evaluation method. A higher setting narrows down the strategies that the AI will consider, leaning towards more aggressive trading. Conversely, a lower setting allows for a more conservative approach by broadening the pool of potential strategies. Optimization Trading system optimization is immensely advantageous when executed with prudence. Technical-oriented, mechanical trading systems work when a valid correlation is methodical to the extent that an objective, precisely-defined ruleset can consistently exploit it. If no such correlation exists, or a technical-oriented system is erroneously designed to exploit an illusory correlation (absent predictive utility), the trading system will fail. Evaluate results practically and test parameters rigorously after discovery. Simply mining the best-performing parameters and immediately trading them is unlikely a winning strategy. Put as much effort into testing strong-performing parameters and building an accompanying system as you would any other trading strategy. Automated optimization involves curve fitting - it's the responsibility of the trader to validate a replicable sequence or correlation and the trading system that exploits it.
Strategi Pine Script®Skrip berbayar
oleh KioseffTrading
21
Kioseff Trading - AI-Optimized RSIAI-Optimized RSI Introducing AI-Optimized RSI: a streamlined solution for traders of any skill level seeking to rapidly test and optimize RSI. Capable of analyzing thousands of strategies, this tool cuts through the complexity to identify the most profitable, reliable, or efficient approaches. Paired with TradingView's native backtesting capabilities, the AI-Optimized RSI learns from historical performance data. Set up is easy for all skill levels, and it makes fine-tuning trading alerts and RSI straightforward. Features Purpose : Uncover optimal RSI settings and entry levels with precision. Say goodbye to random guesses and arbitrary indicator use—this tool provides clear direction based on data. Target Performance : You set the goal, and AI-RSI seeks it out, whether it's maximizing profits, efficient trading, or achieving the highest win rate. AI-Powered : With intelligent AI recommendations, the tool dynamically fine-tunes your RSI approach, steering you towards ideal strategy performance. Rapid Testing : Evaluate thousands of RSI strategies. Dual Direction : Perfect both long and short RSI strategies with equal finesse. Deep Insights : Access detailed metrics including profit factor, PnL, win rate, trade counts, and more, all within a comprehensive strategy script. Instant Alerts : Set alerts and trade. Full Customization : Test and optimize all RSI settings, including cross levels, profit targets and stop losses. Simulated Execution : Explore the impact of limit orders and other trade types through simulation. Integrative Capability : Combine your own custom indicators or others from the TradingView community for a personalized optimization experience. Flexible Timeframes : Set your optimization and backtesting to any date range. Key Settings The image above shows explanations for a list of key settings for the optimizer. Direction : This setting controls trade direction: Long or Short. Entry Condition : Define RSI entry: Select whether to trigger trades on RSI crossunders or crossovers. RSI Lengths Range : Choose the range of RSI periods to test and find the best one.The AI will find the best RSI period for you. RSI Cross Range : Set the range for RSI levels where crosses trigger trade signals. The AI will find the best level for you. Combinations : Select how many RSI strategies to compare. Optimization Type : Choose the goal for optimization and the AI: profit, win rate, or efficiency. Profit Target : Set your profit target with this setting. Stop Loss : Decide your maximum allowable loss (stop loss) per trade. Limit Order : Specify whether to include limit orders in the strategy. Stop Type : Choose your stop strategy: a fixed stop loss or a trailing stop. How to: Find the best RSI for trading It's important to remember that merely having the AI-Optimized RSI on your chart doesn't automatically provide you with the best strategy. You need to follow the AI's guidance through an iterative process to discover the optimal RSI settings and strategy. 1.Starting Your Strategy Setup Begin by deciding your goals for each trade: your profit target and stop loss. You'll also choose how to manage your stops – whether they stay put (fixed) or move with the price (trailing), and whether you want to exit trades at a specific price (limit orders). Keep the initial settings for RSI lengths and cross ranges at their default to give the tool a broad testing field. The AI's guidance will refine these settings to pinpoint the most effective ones through a process of comprehensive testing. The image above shows our chart prior to any optimization efforts. Note: the settings shown above in the key settings section will be used to start our demonstration. 2. Follow AI’s suggestions Optimization Prompt: After loading your strategy, the indicator will prompt you to change the RSI length range and RSI level range to a better performing range. Continue changing the RSI length range and RSI level range to match the indicator's suggestions until "Best Found" is displayed! The image above shows results after we applied the tool’s suggestions. New suggestions have appeared, and we will continue to apply them. Continue to adjust settings as recommended by the optimizer. If no better options are found, the optimizer will suggest increasing the number of combinations. Repeat this process until the optimizer indicates that the optimal setting has been identified. Success! With the "Best Found" notification, an optimized RSI is now active. The AI will keep refining the strategy based on ongoing performance, ensuring continuous optimization. AI Mode AI Mode incorporates Heuristic-Based Adaptive Learning to fine-tune trading strategies in a continuous manner. This feature consists of two main components: Heuristic-Based Decision Making: The algorithm evaluates multiple RSI-based trading strategies using specific metrics such as Profit and Loss (PNL), Win Rate, and Most Efficient Profit. These metrics act as heuristics to assist the algorithm in identifying suitable strategies for trade execution. Online Learning: The algorithm updates the performance evaluations of each strategy based on incoming market data. This enables the system to adapt to current market conditions. Incorporating both heuristic-based decision-making and online learning, this feature aims to provide a framework for trading strategy optimization. Settings AI Mode Aggressiveness: Description: The "AI Mode Aggressiveness" setting allows you to fine-tune the AI's trading behavior. This setting ranges from “Low” to “High”, with “High” indicating a more assertive trading approach. Functionality: This feature filters trading strategies based on a proprietary evaluation method. A higher setting narrows down the strategies that the AI will consider, leaning towards more aggressive trading. Conversely, a lower setting allows for a more conservative approach by broadening the pool of potential strategies. Adaptive Learning Aggressiveness: Description: When Adaptive Learning is enabled, the "Adaptive Learning Aggressiveness" setting controls how dynamically the AI adapts to market conditions using selected performance metrics. Functionality: This setting impacts the AI's responsiveness to shifts in strategy performance. By adjusting this setting, you can control how quickly the AI moves away from strategies that may have been historically successful but are currently underperforming, towards strategies that are showing current promise. Optimization Trading system optimization is immensely advantageous when executed with prudence. Technical-oriented, mechanical trading systems work when a valid correlation is methodical to the extent that an objective, precisely-defined ruleset can consistently exploit it. If no such correlation exists, or a technical-oriented system is erroneously designed to exploit an illusory correlation (absent predictive utility), the trading system will fail. Evaluate results practically and test parameters rigorously after discovery. Simply mining the best-performing parameters and immediately trading them is unlikely a winning strategy. Put as much effort into testing strong-performing parameters and building an accompanying system as you would any other trading strategy. Automated optimization involves curve fitting - it's the responsibility of the trader to validate a replicable sequence or correlation and the trading system that exploits it.
Strategi Pine Script®Skrip berbayar
oleh KioseffTrading
11
AI Market Barometer ProAI Market Barometer Pro - Professional Trading Indicator Overview AI Market Barometer Pro is an advanced multi-timeframe trading system that combines artificial intelligence algorithms with proprietary technical analysis to deliver high-confidence trading signals. This professional-grade indicator analyzes market conditions across multiple timeframes simultaneously, providing traders with clear directional bias and signal strength ratings. Core Features 🎯 Core AI Barometer System - Multi-Timeframe Analysis: Monitors different timeframes simultaneously - AI Confidence Score: Proprietary algorithm calculates signal confidence from 0-100% - Three-Level Signal Strength: Basic, Medium ★, and Strong ★★ signals - Dynamic Background Coloring: Visual market sentiment at a glance - Real-Time Information Panel: Customizable position with live market metrics ⚡ Three AI Accelerator Systems - Accelerator 1: Original multi-timeframe momentum system with 27 dimensions - Accelerator 2: Five-star selection algorithm with 32 AI parameters - Accelerator 3: - Each accelerator provides independent AI support lines and signal zones - Highly selective signals ensuring maximum accuracy 📊 Advanced Visualization - Color-Coded Signals: - Green zones indicate bullish conditions - Red zones indicate bearish conditions - Gray indicates neutral/ranging markets - Smart Labels: Auto-positioned signal labels displaying confidence percentages - Background Intensity: Three levels showing signal strength - Customizable Display: Adjustable panel position and visibility options Configuration Options Display Settings - Panel Position: 9 position options (corners, edges, center) - Show Labels: Toggle signal labels on/off - Show Background Color: Toggle background coloring on/off - Show Info Panel: Toggle real-time information table on/off - Background Display Days: Control how many days of coloring to display (1-30 days) Channel Settings - Enable Channel: Optional channel - Channel Width: Adjustable deviation multiplier Accelerator Settings - Enable Accelerator 1: Original accelerator system - Enable Accelerator 2: Five-star selection system - Enable Accelerator 3: Advanced buy filtering system - Each can be toggled independently Alert System Pre-configured alerts include: - AI Long Signal activation - AI Short Signal activation - AI Ranging Signal activation - Accelerator 1 Bull/Bear zones - Accelerator 2 Bull/Bear zones - Accelerator 3 Bull/Bear zones Information Panel Metrics Real-time display includes: - Current Timeframe - Active Signal (Long/Short/Ranging) - AI Confidence Percentage - Current Price - Change Percentage - Momentum Status (Bullish/Bearish/Mixed) - Signal Strength Rating Recommended Timeframes - Scalping: 1-minute charts - Day Trading: 5-minute, 15-minute charts - Swing Trading: 1-hour, 4-hour, Daily charts - Position Trading: Daily, Weekly charts Technical Requirements - TradingView Pro, Pro+, or Premium account (required for multi-timeframe functionality) - Compatible with all markets: Forex, Crypto, Stocks, Indices, Commodities - Works on all timeframes from 1-minute to Monthly Disclaimer This indicator is a tool to assist with trading decisions. Past performance does not guarantee future results. Trading involves substantial risk of loss. Always use proper risk management and never risk more than you can afford to lose. The AI algorithms and confidence scores are based on historical price patterns and technical analysis, not predictive guarantees. What Makes This Different? Unlike simple trading systems, AI Market Barometer Pro: - ✅ Analyzes multiple timeframes simultaneously - ✅ Calculates dynamic confidence scores - ✅ Provides three-tier signal strength ratings - ✅ Includes three independent accelerator systems - ✅ Delivers highly selective, low-noise signals - ✅ Features professional-grade visualization - ✅ Adapts to all market conditions Join thousands of traders using AI-powered analysis to gain their edge in the markets. 🌤️ Perfect Companion Indicator Enhance your trading with AI Market Weather Forecast Pro Transform complex market analysis into intuitive weather forecasts. Get instant market temperature readings from -50°C to +50°C and know whether you're trading in a heatwave or a blizzard. Why use them together: Barometer → Precise entry/exit signals with AI confidence scores Weather → Overall market climate and trend temperature Combined → Complete market picture for optimal timing 👉 Get AI Market Weather Forecast Pro Know the market climate before you trade. Two indicators, one complete trading system. © 2024 AI Market Barometer Pro. All rights reserved. Proprietary algorithms and methodologies protected.
Penunjuk Pine Script®
oleh max1949
AI Gamma Levels - Options Flow Signals v1.1# AI Gamma Levels - Options Flow Signals ## 📊 Overview An educational indicator that estimates institutional options positioning using price action, volume analysis, and technical indicators. Designed to help traders identify key support and resistance zones based on gamma exposure concepts commonly used by market makers and institutional traders. ## 🎯 Key Features **Gamma Flip Level (⚡)** - Neutral zone where market maker hedging behavior changes - Calculated using VWAP and price action - Acts as dynamic pivot point for intraday trading **Call Wall (🔴)** - Resistance zone from heavy call seller positioning - Identifies where upward price movement may stall - Based on recent highs + ATR-adjusted volatility **Put Support (🟢)** - Support zone from put seller positioning - Shows where downward moves may find buyers - Calculated from recent lows with volatility adjustment **AI Trade Signals (🔮)** - Multi-factor confluence detector with confidence scoring - Only triggers on high-probability setups (70%+ confidence) - Provides clear entry, stop loss, and target levels - Combines gamma regime, RSI, volume, and price proximity **Regime Detection** - Identifies Positive Gamma (bullish bias) vs Negative Gamma (volatile) environments - Background coloring shows current market regime - Helps adapt trading strategy to market conditions **Trading Zone Visualization** - Shaded area between Call Wall and Put Support - Shows expected trading range based on gamma positioning - Zone width indicates market compression or expansion ## 🧠 How AI Signals Work The AI signal layer analyzes multiple factors simultaneously: 1. **Gamma Regime Alignment** - Price position relative to Gamma Flip 2. **Level Proximity** - Distance to Put Support or Call Wall 3. **Momentum Extremes** - Fast RSI showing oversold/overbought 4. **Volume Confirmation** - Above-average volume on the setup 5. **Price Action Quality** - Bar range and volatility characteristics Signals only trigger when ALL conditions align, reducing noise and false signals. **BUY Signal Requirements:** - Price above Gamma Flip (positive regime) - Near Put Support (within 0.5%) - RSI < 35 (oversold) - Volume spike (1.4x average) - Confidence ≥ 70% **SELL Signal Requirements:** - Price below Gamma Flip (negative regime) - Near Call Wall (within 0.5%) - RSI > 65 (overbought) - Volume spike (1.4x average) - Confidence ≥ 70% ## 📈 How to Use **For Day Trading:** - Watch for bounces at Put Support in positive gamma regime - Look for resistance at Call Wall in negative gamma regime - Use AI signals for high-conviction entries with clear risk levels **For Swing Trading:** - Monitor zone width for compression/expansion cycles - Enter when price returns to zone edges with AI confirmation - Use Gamma Flip as trailing stop reference **For Options Traders:** - Identify where institutional gamma is concentrated - Anticipate pinning behavior near expiration - Understand market maker hedging flow impact on price ## ⚙️ Customization **Display Settings:** - Toggle individual levels on/off - Show/hide trading zone shading - Enable/disable AI signals **Calculation Parameters:** - Lookback Period (5-100 bars) - adjusts level sensitivity - Volatility Multiplier (0.5-3.0) - widens/tightens zones - AI Confidence Threshold (60-90%) - signal selectivity **Visual Customization:** - Custom colors for all levels - Adjustable transparency for zones - Label size and positioning ## 📊 Info Table Real-time dashboard showing: - Current Gamma Flip price - Call Wall resistance level - Put Support level - Active gamma regime - Trading zone width (%) - AI signal status and confidence ## 🔔 Built-in Alerts Set alerts for: - Gamma Flip crossovers - Price approaching Call Wall - Price approaching Put Support - AI BUY signal triggered - AI SELL signal triggered ## 📚 Educational Background **What is Gamma Exposure?** Gamma measures how fast market makers must hedge their options positions as price moves. Large gamma concentrations create support/resistance as dealers buy into weakness and sell into strength. **Positive vs Negative Gamma:** - **Positive Gamma** (above Gamma Flip): Market makers hedge by stabilizing price - **Negative Gamma** (below Gamma Flip): Market makers hedge by amplifying moves **Call Walls & Put Supports:** Heavy open interest at specific strikes creates "walls" where price tends to gravitate toward or bounce away from, especially near expiration. ## ⚠️ Important Notes **This indicator uses price and volume approximations**, not real options chain data. It demonstrates gamma exposure concepts for educational purposes. **For true options flow analysis**, consider using platforms with access to real-time open interest, options volume, and Greeks data. **Risk Management:** Always use proper position sizing, stop losses, and never risk more than you can afford to lose. This indicator should be one tool in your complete trading strategy. **Not Financial Advice:** This is an educational tool. Past performance does not guarantee future results. Always do your own research and consider consulting with a qualified financial advisor. ## 💡 Best Practices 1. Combine with your existing strategy - don't trade signals blindly 2. Use on liquid stocks/indices with active options markets 3. Pay attention to regime changes at Gamma Flip crossovers 4. Higher timeframes (15m, 1H, 4H) tend to be more reliable 5. Adjust parameters based on the asset's typical volatility 6. Wait for AI signals with 75%+ confidence for highest quality setups ## 🎓 Who This Is For - Options traders seeking to understand institutional positioning - Day traders looking for high-probability support/resistance - Swing traders identifying key zone boundaries - Anyone interested in learning about gamma exposure impact on price - Traders wanting AI-assisted trade signal confirmation --- **Happy Trading! If you find this indicator helpful, please leave a like and comment with your feedback.**
Penunjuk Pine Script®
oleh GexPro
2
AI Market Weather Forecast ProAI Market Weather Forecast Pro - Advanced Trading Indicator Overview AI Market Weather Forecast Pro is an innovative multi-timeframe trading system that uses global meteorological metaphors to visualize market conditions. By analyzing dimensional latitude regions, it transforms complex market data into intuitive global weather forecasts and temperature readings, helping traders quickly assess market sentiment and trend strength. Core Features 🌍 Global Weather System - Temperature Scale: -51°C to +51°C market temperature readings - Weather Classifications: 9 distinct weather conditions from Freezing Cold to Scorching Heat - Multi-Latitude Analysis: 5 climate zones representing different regional AI parameters - Dynamic Temperature Engine: AI-powered algorithm calculates market "temperature" in real-time - Trend Direction Indicator: Clear bullish/bearish/neutral classification 🌡️ Temperature-Based Signals Hot Weather (Bullish Conditions): - 🌡️ Scorching (35°C+): Strong Bull - Extreme bullish conditions - ☀️ Hot (25°C-35°C): Bullish - Strong upward momentum - 🌤️ Sunny (15°C-25°C): Mild Bull - Moderate bullish trend - ⛅ Partly Cloudy (5°C-15°C): Weak Bull - Light bullish bias Neutral Weather: - ☁️ Overcast (-5°C to 5°C): Neutral - Consolidation/ranging market Cold Weather (Bearish Conditions): - 🌧️ Light Rain (-15°C to -5°C): Weak Bear - Light bearish bias - 🌨️ Sleet (-25°C to -15°C): Mild Bear - Moderate bearish trend - ❄️ Blizzard (-35°C to -25°C): Bearish - Strong downward momentum - 🧊 Freezing Cold (-35°C-): Strong Bear - Extreme bearish conditions 📊 Five Latitude Climate Zones Detects market conditions across 5 distinct "latitude zones", each representing progressively longer timeframes: Each zone displays real-time weather status: ☀️ Clear (bullish), ❄️ Snow (bearish), or ☁️ Cloudy (neutral) 🎨 Advanced Visualization Color-Coded Background: - Orange/Yellow spectrum for bullish temperatures - Gray for neutral conditions - Blue spectrum for bearish temperatures - Intensity increases with temperature extremes Smart Weather Labels: - Emoji-based weather icons for instant recognition - Temperature readings in degrees - Auto-positioned to avoid chart clutter - Updates dynamically with trend changes Comprehensive Weather Panel: - Current weather condition - Market temperature (°C) - Trend direction classification - Real-time status of all 5 latitude zones - Current price and percentage change Configuration Options Display Settings - Panel Position: 9 position options (corners, edges, center) - Show Weather Panel: Toggle weather information panel on/off - Show Background Color: Toggle background coloring on/off - Show Weather Labels: Toggle weather labels on/off - Background Display Days: Control how many days of coloring to display (1-30 days) Alert System Pre-configured alerts include: - Weather Warming: Alert when temperature rises above 15°C - Weather Cooling: Alert when temperature falls below -15°C - Strong Trend Change: Alert when trend shifts to "Strong Bull" or "Strong Bear" Information Panel Metrics Real-time display includes: - Current Weather: Visual weather condition with emoji - Market Temperature: Numerical temperature reading (°C) - Trend Direction: Clear classification (Strong Bull/Bullish/Mild Bull/Weak Bull/Neutral/Weak Bear/Mild Bear/Bearish/Strong Bear) - Latitude Status: Weather conditions across all 5 climate zones - Price & Change: Current price and percentage change How to Interpret Temperature Readings - Above +25°C: Strong bullish conditions, consider long positions - +15°C to +25°C*: Moderate bullish, good for trend following - +5°C to +15°C: Mild bullish, cautious long bias - -5°C to +5°C*: Neutral range, wait for clarity or range trade - -15°C to -5°C: Mild bearish, cautious short bias - -25°C to -15°C: Moderate bearish, good for short positions - Below -25°C: Strong bearish conditions, consider short positions Best Practices 1. Temperature Extremes: Focus on temperatures above +25°C or below -25°C for clear signals 2. Temperature Trend: Watch for rising/falling temperature trends, not just absolute values 3. Combine with Barometer*: Use alongside AI Market Barometer Pro for comprehensive analysis 4. Background Color: Quick visual assessment of overall market climate Recommended Timeframes - Scalping: 1-minute charts - *Day Trading: 5-minute, 15-minute charts Technical Requirements - TradingView Pro, Pro+, or Premium account (required for multi-timeframe functionality) - Compatible with all markets: Forex, Crypto, Stocks, Indices, Commodities - Works on all timeframes from 1-minute to Monthly Disclaimer This indicator is a tool to assist with trading decisions. Past performance does not guarantee future results. Trading involves substantial risk of loss. Always use proper risk management and never risk more than you can afford to lose. The AI algorithms and temperature calculations are based on historical price patterns and technical analysis, not predictive guarantees. What Makes This Different? Unlike traditional indicators, AI Market Weather Forecast Pro: - ✅ Uses intuitive meteorological metaphors for instant comprehension - ✅ Analyzes multiple timeframe combinations simultaneously - ✅ Calculates dynamic market "temperature" readings - ✅ Provides 5-zone latitude system for confirmation - ✅ Offers clear visual weather classifications - ✅ Features unique temperature-based trend strength measurement - ✅ Complements AI Market Barometer Pro for complete market analysis Transform complex multi-timeframe analysis into simple weather forecasts. Know the market climate before you trade. Perfect Companion to AI Market Barometer Pro When used together with AI Market Barometer Pro: - Barometer provides directional signals with AI confidence scores - Weather provides overall market climate and temperature readings - Combined gives you both precise entry signals AND broader market context - Result: More informed trading decisions with better timing © 2024 AI Market Weather Forecast Pro. All rights reserved. Proprietary algorithms and methodologies protected.
Penunjuk Pine Script®
oleh max1949
Big Tech AI vs AI Semi Market Cap Recently, Big Tech stocks have faced downward pressure due to growing concerns over whether they can sustain massive AI CapEx and ultimately achieve monetization. In contrast, AI-related semiconductor stocks—the direct recipients of these investment funds—are rebounding and gaining momentum. Some market participants compare this flow to the Dot-com bubble era. I created this script to track in real-time whether a true "Market Cap Flipping" (reversal) is occurring between the AI Service providers (Big Tech) and the AI Infrastructure providers (Semiconductors). This indicator aggregates and compares the total Market Capitalization (Price × Shares Outstanding) of two distinct groups: 🟦 Big Tech (AI Solutions & Services): The companies spending heavily on AI infrastructure. 🟧 AI Semiconductors (Hardware & Infra): The companies benefiting from Big Tech's CapEx. Real-time Comparison: Visualizes the aggregate value of both sectors on a single chart to spot divergence or convergence. Cap Flipping Watch: Easily identify if the "Hardware" sector's valuation overtakes the "Solution" sector. Percentage Ratio: Displays a label showing the Semiconductor sector's size relative to Big Tech (e.g., "Semi is 60% of Tech"). Customizable Tickers: You can toggle individual companies On/Off in the settings to adjust your basket. Big Tech: MSFT, GOOGL, AMZN, META, AAPL, TSLA, PLTR, ORCL, ADBE AI Semi: NVDA, TSM, AVGO, AMD, MU, ARM, ASML, ANET, MRVL If the Orange Line (Semi) rises while the Blue Line (Tech) falls/stagnates, it indicates the market is favoring "Infrastructure Builders" over "Service Providers." Use this to gauge the maturity of the AI investment cycle.
Penunjuk Pine Script®
oleh KBG86
ICT AI ATR Signals [TradingFinder]🔵 Introduction In financial markets, two main factors always have the greatest impact on traders’ decisions: the direction of the trend and the level of price volatility. Although there are various tools to analyze each of these factors, very few indicators can combine them in a coordinated and simultaneous way. The ICT AI ATR indicator has been designed with this purpose in mind, to provide a unified and comprehensive view of the market instead of relying on multiple scattered indicators. This indicator is built upon two widely used tools: the Moving Average (MA) and the Average True Range (ATR). The combination of these two indicators allows traders to simultaneously track the trend direction and account for market volatility two elements that always play a decisive role in trading decisions. In the structure of the indicator, the Moving Average acts as the central line and serves as the backbone of the tool. By calculating the average price over a defined period, the Moving Average filters out excess market noise and provides a clearer picture of the overall price movement. This helps traders focus on the main trend instead of being distracted by minor and temporary fluctuations. The central line is thus the main reference point for identifying the trend direction. Alongside this, the ATR is responsible for measuring the real volatility of the market. Unlike many tools that only look at closing price changes, the ATR considers the true range of candlestick movements, giving a more accurate view of market dynamics. In the ICT AI ATR indicator, this feature is used to draw dynamic bands above and below the Moving Average line. These bands shift with changing market conditions and act like dynamic support and resistance levels, areas where strong price reactions often occur. This combination allows traders not only to see the dominant market trend through the Moving Average but also to understand volatility and the natural price range via the ATR. For this reason, the ICT AI ATR identifies points that are likely to act as reaction or reversal zones, whether during bounces off the bands or breakouts through them. With this structure, the trader can at a glance : Identify the overall market direction using the Moving Average. Observe volatility and the natural range of price movement through ATR. Recognize key levels where strong reactions or potential reversals are more likely. As a result, the ICT AI ATR functions as a combined tool that replaces the need to use several separate indicators, enabling traders to analyze trend, volatility, price bands, and even Fibonacci targets within a single unified framework. 🔵 How to Use The ICT AI ATR indicator is designed to simplify market analysis through two main components: visual display of bands and signals on the chart itself, and a multi-symbol analytical dashboard capable of monitoring over 20 different assets simultaneously across multiple timeframes. This dashboard feature allows traders to gain a quick overview of overall market conditions without opening multiple charts or constantly switching timeframes. It updates in real-time, showing active Buy (Long) and Sell signals for each symbol. As such, the combination of direct chart display and dashboard analytics makes the indicator useful both for detailed analysis of a single symbol and for monitoring multiple markets at once. 🟣 How do ICT AI ATR trading signals work? Sell Signal (Short) : Triggered when the price pushes below the lower band (Low goes outside the lower band) and then closes back above it. This indicates potential weakness in bullish momentum and suggests possible selling pressure or the start of a downward correction. Traders can use this to spot sell setups or manage long positions. Buy Signal (Long) : Triggered when the price extends above the upper band (High goes outside the upper band) and then closes back below it. This often signals exhaustion in bearish pressure and the return of buying strength, potentially marking the start of a new upward move. This signaling logic is based on the actual behavior of price relative to the ATR dynamic bands. Unlike static formulas, signals adapt to changing market conditions, making them more accurate and reliable. The main advantage of the ICT AI ATR indicator is that traders can benefit from real-time analysis directly on the chart by observing price interactions with the bands and signals while also receiving a multi-market overview through the dashboard. This combination is especially valuable for traders who operate across multiple instruments or markets simultaneously. 🔵 Settings 🟣 Logical settings Moving Average Type : Select the type of moving average for the central line. Options include EMA, SMA, RMA, WMA, or HMA depending on the trading strategy. Moving Average Period : Defines the length of the moving average. Shorter periods make the central line more responsive to price changes, while longer periods smooth out the line to show the broader trend. ATR Period : Determines the number of candles considered for volatility calculation. Shorter periods increase sensitivity, while longer periods provide a more stable view of volatility. ATR Multiplier : Sets the distance between the upper/lower bands and the central moving average line. Higher values widen the bands, while lower values bring them closer to price. Smooth Period: Used to smooth data and reduce chart noise. Higher values produce smoother, more consistent indicator lines. Signal Gap : Defines the minimum number of candles required between two consecutive signals. This prevents back-to-back signals from appearing too frequently and ensures only the more reliable ones are shown. 🟣 Display Settings Table on Chart : Allows users to choose the position of the signal dashboard either directly on the chart or below it, depending on their layout preference. Number of Symbols : Enables users to control how many symbols are displayed in the screener table, from 10 to 20, adjustable in increments of 2 symbols for flexible screening depth. Table Mode : This setting offers two layout styles for the signal table : Basic : Mode displays symbols in a single column, using more vertical space. Extended : Mode arranges symbols in pairs side-by-side, optimizing screen space with a more compact view. Table Size : Lets you adjust the table’s visual size with options such as: auto, tiny, small, normal, large, huge. Table Position : Sets the screen location of the table. Choose from 9 possible positions, combining vertical (top, middle, bottom) and horizontal (left, center, right) alignments. 🟣 Symbol Settings Each of the 10 symbol slots comes with a full set of customizable parameters : Symbol : Define or select the asset (e.g., XAUUSD, BTCUSD, EURUSD, etc.). Timeframe : Set your desired timeframe for each symbol (e.g., 15, 60, 240, 1D). 🟣 Alert Settings Alert : Enables alerts for AAS. Message Frequency : Determines the frequency of alerts. Options include 'All' (every function call), 'Once Per Bar' (first call within the bar), and 'Once Per Bar Close' (final script execution of the real-time bar). Default is 'Once per Bar'. Show Alert Time by Time Zone : Configures the time zone for alert messages. Default is 'UTC'. 🔵 Conclusion The ICT AI ATR indicator, by combining three core elements Moving Average for trend detection, ATR for volatility measurement and dynamic bands, and Fibonacci levels for price targets—provides a multi-layered and intelligent tool for market analysis. In addition to showing accurate bands directly on the chart, it also offers a multi-symbol dashboard that allows traders to monitor signals across different assets and timeframes in real time. The key advantage of this indicator is that it eliminates the need to use several separate tools by integrating trend, volatility, key levels, and trade signals into one unified framework. For this reason, ICT AI ATR is a reliable and effective choice for both short-term traders seeking quick market moves and long-term traders focused on dynamic support and resistance levels.
Penunjuk Pine Script®Skrip berbayar
oleh TFlab
76
AI SwingAI Swing is an indicator that spot overbought over oversold situation. This indicator is specialized for the forex market (but it can be used on the crypto market) Please choose the type of indicator you want to use and choose the chart time accordingly : AI Swing : use the daily chart AI Intraday : use the 1 hour chart AI Scalping : use the 15 minute chart AI Swing est un indicateur qui met en évidence les périodes de sur achat et de sur vente L'indicateur est spécialisé pour le forex (mais il peut être utilisé sur le marché crypto) Choisissez le type d'indicateur que vous voulez utiliser et choisissez le temps du graphique approprié : AI Swing : Utiliser le graphique en journalier AI Intraday : Utiliser le graphique en une heure AI Scalping : Utiliser le graphique en 15 minute
Penunjuk Pine Script®
oleh mentalRock19315