Fibonacci Confluence Toolkit [LuxAlgo]The Fibonacci Confluence Toolkit is a technical analysis tool designed to help traders identify potential price reversal zones by combining key market signals and patterns. It highlights areas of interest where significant price action or reactions are anticipated, automatically applies Fibonacci retracement levels to outline potential pullback zones, and detects engulfing candle patterns.
Its unique strength lies in its reliance solely on price patterns, eliminating the need for user-defined inputs, ensuring a robust and objective analysis of market dynamics.
🔶 USAGE
The script begins by detecting CHoCH (Change of Character) points—key indicators of shifts in market direction. This script integrates the principles of pure price action as applied in Pure-Price-Action-Structures , where further details on the detection process can be found.
The detected CHoCH points serve as the foundation for defining an Area of Interest (AOI), a zone where significant price action or reactions are anticipated.
As new swing highs or lows emerge within the AOI, the tool automatically applies Fibonacci retracement levels to outline potential retracement zones. This setup enables traders to identify areas where price pullbacks may occur, offering actionable insights into potential entries or reversals.
Additionally, the toolkit highlights engulfing candle patterns within these zones, further refining entry points and enhancing confluence for better-informed trading decisions based on real-time trend dynamics and price behavior.
🔶 SETTINGS
🔹 Market Patterns
Bullish Structures: Enable or disable all bullish components of the indicator.
Bearish Structures: Enable or disable all bearish components of the indicator.
Highlight Area of Interest: Toggle the option to highlight the Areas of Interest (enabled or disabled).
CHoCH Line: Choose the line style for the CHoCH (Solid, Dashed, or Dotted).
Width: Adjust the width of the CHoCH line.
🔹 Retracement Levels
Choose which Fibonacci retracement levels to display (e.g., 0, 0.236, 0.382, etc.).
🔹 Swing Levels & Engulfing Patterns
Swing Levels: Select how swing levels are marked (symbols like ◉, △▽, or H/L).
Engulfing Candle Patterns: Choose which engulfing candle patterns to detect (All, Structure-Based, or Disabled).
🔶 RELATED SCRIPTS
Pure-Price-Action-Structures.
Análisis de tendencia
Adaptive Price Zone Oscillator [QuantAlgo]Adaptive Price Zone Oscillator 🎯📊
The Adaptive Price Zone (APZ) Oscillator by QuantAlgo is an advanced technical indicator designed to identify market trends and reversals through adaptive price zones based on volatility-adjusted bands. This sophisticated system combines typical price analysis with dynamic volatility measurements to help traders and investors identify trend direction, potential reversals, and market volatility conditions. By evaluating both price action and volatility together, this tool enables users to make informed trading decisions while adapting to changing market conditions.
💫 Dynamic Zone Architecture
The APZ Oscillator provides a unique framework for assessing market trends through a blend of smoothed typical prices and volatility-based calculations. Unlike traditional oscillators that use fixed parameters, this system incorporates dynamic volatility measurements to adjust sensitivity automatically, helping users determine whether price movements are significant relative to current market conditions. By combining smoothed price trends with adaptive volatility zones, it evaluates both directional movement and market volatility, while the smoothing parameters ensure stable yet responsive signals. This adaptive approach allows users to identify trending conditions while remaining aware of volatility expansions and contractions, enhancing both trend-following and mean-reversion strategies.
📊 Indicator Components & Mechanics
The APZ Oscillator is composed of several technical components that create a dynamic trending system:
Typical Price: Utilizes HLC3 (High, Low, Close average) as a balanced price representation
Volatility Measurement: Computes exponential moving average of price changes to determine dynamic zones
Smoothed Calculations: Applies additional smoothing to reduce noise while maintaining responsiveness
Trend Detection: Evaluates price position relative to adaptive zones to determine market direction
📈 Key Indicators and Features
The APZ Oscillator utilizes typical price with customizable length and threshold parameters to adapt to different trading styles. Volatility calculations are applied to determine zone boundaries, providing context-aware levels for trend identification. The trend detection component evaluates price action relative to the adaptive zones, helping validate trends and identify potential reversals.
The indicator also incorporates multi-layered visualization with:
Color-coded trend representation (bullish/bearish)
Clear trend state indicators (+1/-1)
Mean reversion signals with distinct markers
Gradient fills for better visual clarity
Programmable alerts for trend changes
⚡️ Practical Applications and Examples
✅ Add the Indicator : Add the indicator to your TradingView chart by clicking on the star icon to add it to your favorites ⭐️
👀 Monitor Trend State : Watch the oscillator's position relative to the zero line to identify trend direction and potential reversals. The step-line visualization with diamonds makes trend changes clearly visible.
🎯 Track Signals : Pay attention to the mean reversion markers that appear above and below the price chart:
→ Upward triangles (⤻) signal potential bullish reversals
→ X crosses (↷) indicate potential bearish reversals
🔔 Set Alerts : Configure alerts for trend changes in both bullish and bearish directions, ensuring you can act on significant technical developments promptly.
🌟 Summary and Tips
The Adaptive Price Zone Oscillator by QuantAlgo is a versatile technical tool, designed to support both trend following and mean reversion strategies across different market environments. By combining smoothed typical price analysis with dynamic volatility-based zones, it helps traders and investors identify significant trend changes while measuring market volatility, providing reliable technical signals. The tool's adaptability through customizable length, threshold, and smoothing parameters makes it suitable for various trading timeframes and styles, allowing users to capture opportunities while maintaining awareness of changing market conditions.
Key parameters to optimize for your trading style:
APZ Length: Adjust for more or less sensitivity to price changes
Threshold: Fine-tune the volatility multiplier for wider or narrower zones
Smoothing: Balance noise reduction with signal responsiveness
Linear Regression Channel [TradingFinder] Existing Trend Line🔵 Introduction
The Linear Regression Channel indicator is one of the technical analysis tool, widely used to identify support, resistance, and analyze upward and downward trends.
The Linear Regression Channel comprises five main components : the midline, representing the linear regression line, and the support and resistance lines, which are calculated based on the distance from the midline using either standard deviation or ATR.
This indicator leverages linear regression to forecast price changes based on historical data and encapsulates price movements within a price channel.
The upper and lower lines of the channel, which define resistance and support levels, assist traders in pinpointing entry and exit points, ultimately aiding better trading decisions.
When prices approach these channel lines, the likelihood of interaction with support or resistance levels increases, and breaking through these lines may signal a price reversal or continuation.
Due to its precision in identifying price trends, analyzing trend reversals, and determining key price levels, the Linear Regression Channel indicator is widely regarded as a reliable tool across financial markets such as Forex, stocks, and cryptocurrencies.
🔵 How to Use
🟣 Identifying Entry Signals
One of the primary uses of this indicator is recognizing buy signals. The lower channel line acts as a support level, and when the price nears this line, the likelihood of an upward reversal increases.
In an uptrend : When the price approaches the lower channel line and signs of upward reversal (e.g., reversal candlesticks or high trading volume) are observed, it is considered a buy signal.
In a downtrend : If the price breaks the lower channel line and subsequently re-enters the channel, it may signal a trend change, offering a buying opportunity.
🟣 Identifying Exit Signals
The Linear Regression Channel is also used to identify sell signals. The upper channel line generally acts as a resistance level, and when the price approaches this line, the likelihood of a price decrease increases.
In an uptrend : Approaching the upper channel line and observing weakness in the uptrend (e.g., declining volume or reversal patterns) indicates a sell signal.
In a downtrend : When the price reaches the upper channel line and reverses downward, this is considered a signal to exit trades.
🟣 Analyzing Channel Breakouts
The Linear Regression Channel allows traders to identify price breakouts as strong signals of potential trend changes.
Breaking the upper channel line : Indicates buyer strength and the likelihood of a continued uptrend, often accompanied by increased trading volume.
Breaking the lower channel line : Suggests seller dominance and the possibility of a continued downtrend, providing a strong sell signal.
🟣 Mean Reversion Analysis
A key concept in using the Linear Regression Channel is the tendency for prices to revert to the midline of the channel, which acts as a dynamic moving average, reflecting the price's equilibrium over time.
In uptrends : Significant deviations from the midline increase the likelihood of a price retracement toward the midline.
In downtrends : When prices deviate considerably from the midline, a return toward the midline can be used to identify potential reversal points.
🔵 Settings
🟣 Time Frame
The time frame setting enables users to view higher time frame data on a lower time frame chart. This feature is especially useful for traders employing multi-time frame analysis.
🟣 Regression Type
Standard : Utilizes classical linear regression to draw the midline and channel lines.
Advanced : Produces similar results to the standard method but may provide slightly different alignment on the chart.
🟣 Scaling Type
Standard Deviation : Suitable for markets with stable volatility.
ATR (Average True Range) : Ideal for markets with higher volatility.
🟣 Scaling Coefficients
Larger coefficients create broader channels for broader trend analysis.
Smaller coefficients produce tighter channels for precision analysis.
🟣 Channel Extension
None : No extension.
Left: Extends lines to the left to analyze historical trends.
Right : Extends lines to the right for future predictions.
Both : Extends lines in both directions.
🔵 Conclusion
The Linear Regression Channel indicator is a versatile and powerful tool in technical analysis, providing traders with support, resistance, and midline insights to better understand price behavior. Its advanced settings, including time frame selection, regression type, scaling options, and customizable coefficients, allow for tailored and precise analysis.
One of its standout advantages is its ability to support multi-time frame analysis, enabling traders to view higher time frame data within a lower time frame context. The option to use scaling methods like ATR or standard deviation further enhances its adaptability to markets with varying volatility.
Designed to identify entry and exit signals, analyze mean reversion, and assess channel breakouts, this indicator is suitable for a wide range of markets, including Forex, stocks, and cryptocurrencies. By incorporating this tool into your trading strategy, you can make more informed decisions and improve the accuracy of your market predictions.
Swing High/Low Pivots Strategy [LV]The Swing High/Low Pivots Strategy was developed as a counter-momentum trading tool.
The strategy is suitable for any market and its default input values are set to fit BTC 15min.
Check tooltips in the settings menu for more details about user inputs.
Trades Entry based on the detection of swing highs and lows for short and long entries respectively, validated by:
Limit orders placed after each new pivot level confirmation
Moving averages trend filter (if enabled)
No active trade
Trades Exit when the price reaches take-profit or stop-loss level as defined in the settings menu. A double entry/second take-profit level can be enabled for partial exits, with dynamic stop-loss adjustment for the remaining position.
Swing High/Low Pivot Detection
Employs ta.pivothigh and ta.pivotlow to detect higher highs (HH), lower highs (LH), higher lows (HL), and lower lows (LL).
Trend Filter
Integrates a moving average filter to validate trade entries based on the current trend observed at Pivot. Supports multiple moving average types, including EMA, SMA, WMA, HMA, VWMA, VWAP, and more.
Alerts
Configurable alert messages are suitable for API use.
Visuals
Moving average
Pivot markers
Limit lines
Stop-loss
Take-profit
Any feedback, comments, or suggestions for improvement are always welcome.
Hope you enjoy ;)
Loacally Weighted MA (LWMA) Direction HistogramThe Locally Weighted Moving Average (LWMA) Direction Histogram indicator is designed to provide traders with a visual representation of the price momentum and trend direction. This Pine Script, written in version 6, calculates an LWMA by assigning higher weights to recent data points, emphasizing the most current market movements. The script incorporates user-defined input parameters, such as the LWMA length and a direction lookback period, making it flexible to adapt to various trading strategies and preferences.
The histogram visually represents the difference between the current LWMA and a previous LWMA value (based on the lookback period). Positive values are colored blue, indicating upward momentum, while negative values are yellow, signaling downward movement. Additionally, the script colors candlesticks according to the histogram's value, enhancing clarity for users analyzing market trends. The LWMA line itself is plotted on the chart but hidden by default, enabling traders to toggle its visibility as needed. This blend of histogram and candlestick visualization offers a comprehensive tool for identifying shifts in momentum and potential trading opportunities.
Algorithmic Signal AnalyzerMeet Algorithmic Signal Analyzer (ASA) v1: A revolutionary tool that ushers in a new era of clarity and precision for both short-term and long-term market analysis, elevating your strategies to the next level.
ASA is an advanced TradingView indicator designed to filter out noise and enhance signal detection using mathematical models. By processing price movements within defined standard deviation ranges, ASA produces a smoothed analysis based on a Weighted Moving Average (WMA). The Volatility Filter ensures that only relevant price data is retained, removing outliers and improving analytical accuracy.
While ASA provides significant analytical advantages, it’s essential to understand its capabilities in both short-term and long-term use cases. For short-term trading, ASA excels at capturing swift opportunities by highlighting immediate trend changes. Conversely, in long-term trading, it reveals the overall direction of market trends, enabling traders to align their strategies with prevailing conditions.
Despite these benefits, traders must remember that ASA is not designed for precise trade execution systems where accuracy in timing and price levels is critical. Its focus is on analysis rather than order management. The distinction is crucial: ASA helps interpret price action effectively but may not account for real-time market factors such as slippage or execution delays.
Features and Functionality
ASA integrates multiple tools to enhance its analytical capabilities:
Customizable Moving Averages: SMA, EMA, and WMA options allow users to tailor the indicator to their trading style.
Signal Detection: Identifies bullish and bearish trends using the Relative Exponential Moving Average (REMA) and marks potential buy/sell opportunities.
Visual Aids: Color-coded trend lines (green for upward, red for downward) simplify interpretation.
Alert System: Notifications for trend swings and reversals enable timely decision-making.
Notes on Usage
ASA’s effectiveness depends on the context in which it is applied. Traders should carefully consider the trade-offs between analysis and execution.
Results may vary depending on market conditions and chart types. Backtesting with ASA on standard charts provides more reliable insights compared to non-standard chart types.
Short-term use focuses on rapid trend recognition, while long-term application emphasizes understanding broader market movements.
Takeaways
ASA is not a tool for precise trade execution but a powerful aid for interpreting price trends.
For short-term trading, ASA identifies quick opportunities, while for long-term strategies, it highlights trend directions.
Understanding ASA’s limitations and strengths is key to maximizing its utility.
ASA is a robust solution for traders seeking to filter noise, enhance analytical clarity, and align their strategies with market movements, whether for short bursts of activity or sustained trading goals.
Zero-Lag MA CandlesThe Zero-Lag MA Candles indicator combines the efficiency of a Zero-Lag Moving Average (ZLMA) with dynamic candlestick coloring to provide a clear visual representation of market trends. By leveraging a dual EMA-based calculation, the ZLMA achieves reduced lag, enhancing its responsiveness to price changes. The indicator plots candles on the chart with colors determined by the trend direction of the ZLMA over a user-defined lookback period. Blue candles signify an uptrend, while yellow candles indicate a downtrend, offering traders an intuitive way to identify market sentiment.
This indicator is particularly useful for trend-following strategies, as the crossover and crossunder between the ZLMA and the standard EMA highlight potential reversal points or trend continuation zones. With customizable inputs for ZLMA length, trend lookback period, and color schemes, it caters to diverse trading preferences. Its ability to plot directly on the chart ensures seamless integration with other analysis tools, making it a valuable addition to a trader's toolkit.
Happy trading...
Sameer Open Interest IndicatorThe script is a copy of Original Open interest indicator but resolved few bugs so that it start working again. It shows Open interest for the option symbol you have selected . This is experimental script and one should always go to authenticated source for data and decision making . This script is only useful for educational purpose and author is not liable for any moral or legal consequences . Any type of loss or harm by use of this indicator is sole responsibility of user and not that of author or trading view . Please use with caution. The script can change and terms can be updated anytime . The script can be deleted and stopped from using anytime.
Prediction Based on Linreg & Atr
We created this algorithm with the goal of predicting future prices 📊, specifically where the value of any asset will go in the next 20 periods ⏳. It uses linear regression based on past prices, calculating a slope and an intercept to forecast future behavior 🔮. This prediction is then adjusted according to market volatility, measured by the ATR 📉, and the direction of trend signals, which are based on the MACD and moving averages 📈.
How Does the Linreg & ATR Prediction Work?
1. Trend Calculation and Signals:
o Technical Indicators: We use short- and long-term exponential moving averages (EMA), RSI, MACD, and Bollinger Bands 📊 to assess market direction and sentiment (not visually presented in the script).
o Calculation Functions: These include functions to calculate slope, average, intercept, standard deviation, and Pearson's R, which are crucial for regression analysis 📉.
2. Predicting Future Prices:
o Linear Regression: The algorithm calculates the slope, average, and intercept of past prices to create a regression channel 📈, helping to predict the range of future prices 🔮.
o Standard Deviation and Pearson's R: These metrics determine the strength of the regression 🔍.
3. Adjusting the Prediction:
o The predicted value is adjusted by considering market volatility (ATR 📉) and the direction of trend signals 🔮, ensuring that the prediction is aligned with the current market environment 🌍.
4. Visualization:
o Prediction Lines and Bands: The algorithm plots lines that display the predicted future price along with a prediction range (upper and lower bounds) 📉📈.
5. EMA Cross Signals:
o EMA Conditions and Total Score: A bullish crossover signal is generated when the total score is positive and the short EMA crosses above the long EMA 📈. A bearish crossover signal is generated when the total score is negative and the short EMA crosses below the long EMA 📉.
6. Additional Considerations:
o Multi-Timeframe Regression Channel: The script calculates regression channels for different timeframes (5m, 15m, 30m, 4h) ⏳, helping determine the overall market direction 📊 (not visually presented).
Confidence Interpretation:
• High Confidence (close to 100%): Indicates strong alignment between timeframes with a clear trend (bullish or bearish) 🔥.
• Low Confidence (close to 0%): Shows disagreement or weak signals between timeframes ⚠️.
Confidence complements the interpretation of the prediction range and expected direction 🔮, aiding in decision-making for market entry or exit 🚀.
Español
Creamos este algoritmo con el objetivo de predecir los precios futuros 📊, específicamente hacia dónde irá el valor de cualquier activo en los próximos 20 períodos ⏳. Utiliza regresión lineal basada en los precios pasados, calculando una pendiente y una intersección para prever el comportamiento futuro 🔮. Esta predicción se ajusta según la volatilidad del mercado, medida por el ATR 📉, y la dirección de las señales de tendencia, que se basan en el MACD y las medias móviles 📈.
¿Cómo Funciona la Predicción con Linreg & ATR?
Cálculo de Tendencias y Señales:
Indicadores Técnicos: Usamos medias móviles exponenciales (EMA) a corto y largo plazo, RSI, MACD y Bandas de Bollinger 📊 para evaluar la dirección y el sentimiento del mercado (no presentados visualmente en el script).
Funciones de Cálculo: Incluye funciones para calcular pendiente, media, intersección, desviación estándar y el coeficiente de correlación de Pearson, esenciales para el análisis de regresión 📉.
Predicción de Precios Futuros:
Regresión Lineal: El algoritmo calcula la pendiente, la media y la intersección de los precios pasados para crear un canal de regresión 📈, ayudando a predecir el rango de precios futuros 🔮.
Desviación Estándar y Pearson's R: Estas métricas determinan la fuerza de la regresión 🔍.
Ajuste de la Predicción:
El valor predicho se ajusta considerando la volatilidad del mercado (ATR 📉) y la dirección de las señales de tendencia 🔮, asegurando que la predicción esté alineada con el entorno actual del mercado 🌍.
Visualización:
Líneas y Bandas de Predicción: El algoritmo traza líneas que muestran el precio futuro predicho, junto con un rango de predicción (límites superior e inferior) 📉📈.
Señales de Cruce de EMAs:
Condiciones de EMAs y Puntaje Total: Se genera una señal de cruce alcista cuando el puntaje total es positivo y la EMA corta cruza por encima de la EMA larga 📈. Se genera una señal de cruce bajista cuando el puntaje total es negativo y la EMA corta cruza por debajo de la EMA larga 📉.
Consideraciones Adicionales:
Canal de Regresión Multi-Timeframe: El script calcula canales de regresión para diferentes marcos de tiempo (5m, 15m, 30m, 4h) ⏳, ayudando a determinar la dirección general del mercado 📊 (no presentado visualmente).
Interpretación de la Confianza:
Alta Confianza (cerca del 100%): Indica una fuerte alineación entre los marcos temporales con una tendencia clara (alcista o bajista) 🔥.
Baja Confianza (cerca del 0%): Muestra desacuerdo o señales débiles entre los marcos temporales ⚠️.
La confianza complementa la interpretación del rango de predicción y la dirección esperada 🔮, ayudando en las decisiones de entrada o salida en el mercado 🚀.
AUTO GRID HORIZONTAL LINES (what you're looking 4)ESPAÑOL
Este indicador crea líneas horizontales basadas en los niveles de High y Low de un rango de días seleccionado, dividiendo la distancia entre ellas en partes iguales. Es ideal para visualizar zonas de soporte y resistencia de manera rápida y clara en cualquier marco temporal. Puedes ajustar el número de líneas y la distancia entre ellas según lo necesites. ¡Es perfecto para identificar niveles clave de precios de forma sencilla y efectiva!
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This indicator draws horizontal lines based on the High and Low levels of a selected range of days, evenly dividing the space between them. It’s great for quickly and clearly visualizing support and resistance zones on any timeframe. You can adjust the number of lines and the distance between them as needed. Perfect for identifying key price levels in a simple and effective way!
VuTu HalfTrend + Tma indicator Indicator chỉ là 1 công cụ hỗ trợ giống như là thêm 1 chiếc bút chì trong hộp màu của bạn. Hãy tự do sáng tạo và kết hợp để phù hợp nhất cho bản thân và tối ưu chiến lược của mình.ggwp
This indicator is a cool combo of the half-trend methodology and TMA Centered Bands. The main idea is to help spot where the market is trending and where it might be reversing by using a mix of moving averages and the highest and lowest price data values.
MS + ZigZag [TradingFinder] CHoCH/BOS - MSS/MSB+7_EMAThis is edited from Market structure Zigzag TradingFinder by Add more 7 EMAs to chart.
You can edit or change EMAs value or any.
AiTrend Pattern Matrix for kNN Forecasting (AiBitcoinTrend)The AiTrend Pattern Matrix for kNN Forecasting (AiBitcoinTrend) is a cutting-edge indicator that combines advanced mathematical modeling, AI-driven analytics, and segment-based pattern recognition to forecast price movements with precision. This tool is designed to provide traders with deep insights into market dynamics by leveraging multivariate pattern detection and sophisticated predictive algorithms.
👽 Core Features
Segment-Based Pattern Recognition
At its heart, the indicator divides price data into discrete segments, capturing key elements like candle bodies, high-low ranges, and wicks. These segments are normalized using ATR-based volatility adjustments to ensure robustness across varying market conditions.
AI-Powered k-Nearest Neighbors (kNN) Prediction
The predictive engine uses the kNN algorithm to identify the closest historical patterns in a multivariate dictionary. By calculating the distance between current and historical segments, the algorithm determines the most likely outcomes, weighting predictions based on either proximity (distance) or averages.
Dynamic Dictionary of Historical Patterns
The indicator maintains a rolling dictionary of historical patterns, storing multivariate data for:
Candle body ranges, High-low ranges, Wick highs and lows.
This dynamic approach ensures the model adapts continuously to evolving market conditions.
Volatility-Normalized Forecasting
Using ATR bands, the indicator normalizes patterns, reducing noise and enhancing the reliability of predictions in high-volatility environments.
AI-Driven Trend Detection
The indicator not only predicts price levels but also identifies market regimes by comparing current conditions to historically significant highs, lows, and midpoints. This allows for clear visualizations of trend shifts and momentum changes.
👽 Deep Dive into the Core Mathematics
👾 Segment-Based Multivariate Pattern Analysis
The indicator analyzes price data by dividing each bar into distinct segments, isolating key components such as:
Body Ranges: Differences between the open and close prices.
High-Low Ranges: Capturing the full volatility of a bar.
Wick Extremes: Quantifying deviations beyond the body, both above and below.
Each segment contributes uniquely to the predictive model, ensuring a rich, multidimensional understanding of price action. These segments are stored in a rolling dictionary of patterns, enabling the indicator to reference historical behavior dynamically.
👾 Volatility Normalization Using ATR
To ensure robustness across varying market conditions, the indicator normalizes patterns using Average True Range (ATR). This process scales each component to account for the prevailing market volatility, allowing the algorithm to compare patterns on a level playing field regardless of differing price scales or fluctuations.
👾 k-Nearest Neighbors (kNN) Algorithm
The AI core employs the kNN algorithm, a machine-learning technique that evaluates the similarity between the current pattern and a library of historical patterns.
Euclidean Distance Calculation:
The indicator computes the multivariate distance across four distinct dimensions: body range, high-low range, wick low, and wick high. This ensures a comprehensive and precise comparison between patterns.
Weighting Schemes: The contribution of each pattern to the forecast is either weighted by its proximity (distance) or averaged, based on user settings.
👾 Prediction Horizon and Refinement
The indicator forecasts future price movements (Y_hat) by predicting logarithmic changes in the price and projecting them forward using exponential scaling. This forecast is smoothed using a user-defined EMA filter to reduce noise and enhance actionable clarity.
👽 AI-Driven Pattern Recognition
Dynamic Dictionary of Patterns: The indicator maintains a rolling dictionary of N multivariate patterns, continuously updated to reflect the latest market data. This ensures it adapts seamlessly to changing market conditions.
Nearest Neighbor Matching: At each bar, the algorithm identifies the most similar historical pattern. The prediction is based on the aggregated outcomes of the closest neighbors, providing confidence levels and directional bias.
Multivariate Synthesis: By combining multiple dimensions of price action into a unified prediction, the indicator achieves a level of depth and accuracy unattainable by single-variable models.
Visual Outputs
Forecast Line (Y_hat_line):
A smoothed projection of the expected price trend, based on the weighted contribution of similar historical patterns.
Trend Regime Bands:
Dynamic high, low, and midlines highlight the current market regime, providing actionable insights into momentum and range.
Historical Pattern Matching:
The nearest historical pattern is displayed, allowing traders to visualize similarities
👽 Applications
Trend Identification:
Detect and follow emerging trends early using dynamic trend regime analysis.
Reversal Signals:
Anticipate market reversals with high-confidence predictions based on historically similar scenarios.
Range and Momentum Trading:
Leverage multivariate analysis to understand price ranges and momentum, making it suitable for both breakout and mean-reversion strategies.
Disclaimer: This information is for entertainment purposes only and does not constitute financial advice. Please consult with a qualified financial advisor before making any investment decisions.
Güçlendirilmiş Al/Sat Sinyalleri - Enhanced Trading SignalsBu gösterge, piyasalardaki güçlü trendleri tespit etmek ve doğru zamanlı al/sat sinyalleri üretmek için geliştirilmiştir. Aşağıdaki teknik analiz araçlarını birleştirir:
EMA (Üssel Hareketli Ortalama): Trend yönünü filtrelemek için kullanılır.
Bollinger Bantları: Fiyat dalgalanmalarını ve aşırı alım/satım bölgelerini tespit eder.
MACD (Hareketli Ortalama Yakınsama Uzaklaşma): Momentum ve trend dönüşlerini analiz eder.
RSI (Göreceli Güç Endeksi): Aşırı alım/satım seviyelerini belirler.
ADX (Ortalama Yönsel İndeks): Trendin gücünü ölçer.
VWMA (Hacim Ağırlıklı Hareketli Ortalama): Fiyat hareketlerini hacimle birlikte değerlendirir.
CCI (Emtia Kanal Endeksi): Fiyatın aşırı alım veya satımda olup olmadığını gösterir.
Stokastik RSI: Fiyatın hızını ve aşırı durumlarını değerlendirir.
Ichimoku Bulutu: Trend yönü ve destek/direnç seviyelerini tespit eder.
Pivot Noktaları: Potansiyel dönüş noktalarını belirler.
Gösterge, bu araçları birleştirerek yalnızca güçlü trendlerde sinyaller üretir. Sinyaller:
LONG (AL): Fiyat güçlü bir trendin yukarı yönünde olduğunu gösterdiğinde oluşur.
SHORT (SAT): Fiyat güçlü bir trendin aşağı yönünde olduğunu gösterdiğinde oluşur.
Ek olarak, özel semboller (🚀 ve 🔥), MACD kesişmelerini gösterir.
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This indicator is designed to identify strong market trends and provide accurate buy/sell signals. It integrates the following technical analysis tools:
EMA (Exponential Moving Average): Filters trend direction.
Bollinger Bands: Identifies price volatility and overbought/oversold zones.
MACD (Moving Average Convergence Divergence): Analyzes momentum and trend reversals.
RSI (Relative Strength Index): Detects overbought/oversold conditions.
ADX (Average Directional Index): Measures trend strength.
VWMA (Volume Weighted Moving Average): Evaluates price movements with volume.
CCI (Commodity Channel Index): Highlights overbought/oversold price levels.
Stochastic RSI: Assesses price momentum and extremes.
Ichimoku Cloud: Identifies trend direction and support/resistance levels.
Pivot Points: Determines potential reversal zones.
The indicator combines these tools to generate signals only during strong trends. Signals:
LONG (BUY): Triggered when the price confirms an upward trend.
SHORT (SELL): Triggered when the price confirms a downward trend.
Additionally, custom icons (🚀 and 🔥) indicate MACD crossovers.
Simple Backtester for LuxAlgo® Signals & Overlays™This Pine Script™ code is subject to the terms of the Mozilla Public License 2.0 at mozilla.org
© Chart0bserver
This strategy is NOT from the LuxAlgo® developers. We created this to compliment their hard work. No association with LuxAlgo® is intended nor implied.
Please visit chart.observer to test your Tradingview Strategies in our paper-trading sandbox environment. Webhook your alerts to our API. Past performance does not ensure future results. This strategy provided with absolutely no warranty and is for educational purposes only
The goal of this strategy is to enter a long position using the Custom Alert condition feature of LuxAlgo® Signals & Overlays™ indicator.
To trigger an exit from the long position, use one or more of the common exit signals which the Signals & Overlays™ indicator provides. You will need to connect those signals to this strategy in the Inputs dialog box.
We're calling this a "piggyback" strategy because the LuxAlgo® Signals & Overlays indicator must be present, and remain on the chart.
The Signals and Overlays™ indicator is invite-only, and requires a paid subscription from LuxAlgo® - luxalgo.com
MA Direction Histogram
The MA Direction Histogram is a simple yet powerful tool for visualizing the momentum of a moving average (MA). It highlights whether the MA is trending up or down, making it ideal for identifying market direction quickly.
Key Features:
1. Custom MA Options: Choose from SMA, EMA, WMA, VWMA, or HMA for flexible analysis.
2. Momentum Visualization: Bars show the difference between the MA and its value from a lookback period.
- Blue Bars: Upward momentum.
- Yellow Bars: Downward momentum.
3. Easy Customization: Adjust the MA length, lookback period, and data source.
How to Use:
- Confirm Trends: Positive bars indicate uptrends; negative bars suggest downtrends.
- *Spot Reversals: Look for bar color changes as potential reversal signals.
Compact, intuitive, and versatile, the "MA Direction Histogram" helps traders stay aligned with market momentum. Perfect for trend-based strategies!
Key LevelsKey Levels Indicator
In the world of trading, manually identifying and plotting key levels for every close can be a tedious and error-prone task. This indicator stands out by automatically detecting and plotting only those levels where a significant shift in market sentiment has occurred. Unlike traditional indicators that plot lines for every open or close, this tool focuses on levels where liquidity has changed hands, indicating a potential shift in momentum.
How It Works:
- The indicator identifies Higher Timeframe (HTF) reversals, plotting levels only when a bearish candle is followed by a bullish one, or vice versa.
- Weekly levels are represented by dashed lines, while monthly levels are solid, providing clear visual differentiation.
- Levels are drawn at the open price of the reversal candle, starting precisely at the beginning of the new HTF bar.
Why It's Different:
- Focuses on genuine shifts in market sentiment rather than arbitrary price points.
- Automatically manages the number of visible levels to prevent chart clutter.
- Ideal for range traders and mean reversion strategies, offering insights into potential support and resistance zones where market participants have shown a change in behavior.
Usage Note:
While this indicator provides valuable insights, it should not be used in isolation. Always consider the broader market context and combine it with other analysis techniques for optimal results.
Settings:
- Toggle weekly/monthly levels
- Adjust the number of visible levels (1-20)
- Customize level colors
Price Volume TrendlineThe Price Volume Trendline indicator calculates and displays a linear regression trendline based on the product of volume and price (e.g., Volume * Close, Volume * Open, etc.) for a specified timeframe. The indicator helps visualize the relationship between price and volume movements over time.
Note - Please choose a timeframe to display the trendline.
Key Features:
Linear Regression: The trendline is computed using a linear regression of Volume * Price values over a user-defined length (length_trend), providing a smoothed representation of the trend.
Color Coding: The trendline color changes dynamically:
Green: When the slope of the trendline is positive (indicating an uptrend in Volume * Price).
Red: When the slope of the trendline is negative (indicating a downtrend in Volume * Price).
Customizable Timeframe: Users can choose the timeframe for the Volume * Price calculation (either "auto" for the chart's timeframe or a custom timeframe).
This indicator is useful for identifying long-term trends in the relationship between price and volume, highlighting bullish or bearish conditions based on both price and volume dynamics.
Please feel free to share your feedback. That would be appreciated!
Improved Indicators Table with AlertsThe provided Pine Script code appears to be a custom technical indicator for trading purposes. It defines several technical indicators like RSI, ADX, MACD, EMA, and ATR, and displays them in a table format along with their corresponding trend or market condition. Additionally, it plots various EMAs on the chart and generates alerts for EMA crossovers.
Here's a breakdown of the script functionalities:
Inputs:
Defines various input parameters for customizing the indicators (lengths, smoothing periods, etc.)
Options to control breakouts, volume thresholds, and pivot points for support and resistance levels.
Calculations:
Calculates various technical indicators based on user-defined parameters.
Analyzes price movements and volume to determine market conditions (trending or consolidating).
Identifies potential breakouts based on price crossing support/resistance levels and volume.
Outputs:
Displays a table with indicator values, trend direction, and market condition with color-coded backgrounds for better visualization.
Plots short, long, fast, and slow EMAs on the chart.
Generates alerts for bullish/bearish crossovers between fast and slow EMAs.
Plots shapes and labels to indicate potential breakouts and wick formations.
Triggers alerts for support and resistance breakouts with sufficient volume.
Overall, this script aims to provide traders with a comprehensive view of various technical analysis indicators and potential trading signals based on price, volume, and momentum.
Disclaimer: I am unable to provide financial advice. This script is for educational purposes only, and its trading signals should not be considered financial recommendations.
1X_Super_Trader_SD//@version=6
indicator('1X_Super_Trader_SD', overlay = true)
Periods = input(title = 'ATR Period', defval = 10)
src = input(hl2, title = 'Source')
Multiplier = input.float(title = 'ATR Multiplier', step = 0.1, defval = 1.8)
changeATR = input(title = 'Change ATR Calculation Method ?', defval = true)
showsignals = input(title = 'Show Buy/Sell Signals ?', defval = true)
atr2 = ta.sma(ta.tr, Periods)
atr = changeATR ? ta.atr(Periods) : atr2
up = src - Multiplier * atr
up1 = nz(up , up)
up := close > up1 ? math.max(up, up1) : up
dn = src + Multiplier * atr
dn1 = nz(dn , dn)
dn := close < dn1 ? math.min(dn, dn1) : dn
trend = 1
trend := nz(trend , trend)
trend := trend == -1 and close > dn1 ? 1 : trend == 1 and close < up1 ? -1 : trend
upPlot = plot(trend == 1 ? up : na, title = 'Up Trend', style = plot.style_linebr, linewidth = 2, color = color.new(color.green, 0))
buySignal = trend == 1 and trend == -1
plotshape(buySignal ? up : na, title = 'UpTrend Begins', location = location.absolute, style = shape.circle, size = size.tiny, color = color.new(color.green, 0))
plotshape(buySignal and showsignals ? up : na, title = 'Buy', text = 'Buy', location = location.absolute, style = shape.labelup, size = size.tiny, color = color.new(color.green, 0), textcolor = color.new(color.white, 0))
dnPlot = plot(trend == 1 ? na : dn, title = 'Down Trend', style = plot.style_linebr, linewidth = 2, color = color.new(color.red, 0))
sellSignal = trend == -1 and trend == 1
plotshape(sellSignal ? dn : na, title = 'DownTrend Begins', location = location.absolute, style = shape.circle, size = size.tiny, color = color.new(color.red, 0))
plotshape(sellSignal and showsignals ? dn : na, title = 'Sell', text = 'Sell', location = location.absolute, style = shape.labeldown, size = size.tiny, color = color.new(color.red, 0), textcolor = color.new(color.white, 0))
alertcondition(buySignal, title = 'SuperTrend Buy', message = 'SuperTrend Buy!')
alertcondition(sellSignal, title = 'SuperTrend Sell', message = 'SuperTrend Sell!')
changeCond = trend != trend
alertcondition(changeCond, title = 'SuperTrend Direction Change', message = 'SuperTrend has changed direction!')
VWAP + RSI Strong Buy/Sell SignalsPine Script that generates strong buy and sell signals based on VWAP (Volume Weighted Average Price) and RSI (Relative Strength Index). This combines trend-following (VWAP) and momentum-based (RSI) indicators for precise signals.
Strategy Logic:
Buy Signal:
Price is above the VWAP.
RSI is oversold (below 30).
Sell Signal:
Price is below the VWAP.
RSI is overbought (above 70).
Trend Chance Indicator by YanilmazTrend change Indicator: If you wish, you can remove the backround and change the moving avarage setting to 50.
1X_Super_Trader_SD//@version=6
indicator('1X_Super_Trader_SD', overlay = true)
Periods = input(title = 'ATR Period', defval = 10)
src = input(hl2, title = 'Source')
Multiplier = input.float(title = 'ATR Multiplier', step = 0.1, defval = 3.0)
changeATR = input(title = 'Change ATR Calculation Method ?', defval = true)
showsignals = input(title = 'Show Buy/Sell Signals ?', defval = true)
highlighting = input(title = 'Highlighter On/Off ?', defval = true)
atr2 = ta.sma(ta.tr, Periods)
atr = changeATR ? ta.atr(Periods) : atr2
up = src - Multiplier * atr
up1 = nz(up , up)
up := close > up1 ? math.max(up, up1) : up
dn = src + Multiplier * atr
dn1 = nz(dn , dn)
dn := close < dn1 ? math.min(dn, dn1) : dn
trend = 1
trend := nz(trend , trend)
trend := trend == -1 and close > dn1 ? 1 : trend == 1 and close < up1 ? -1 : trend
upPlot = plot(trend == 1 ? up : na, title = 'Up Trend', style = plot.style_linebr, linewidth = 2, color = color.new(color.green, 0))
buySignal = trend == 1 and trend == -1
plotshape(buySignal ? up : na, title = 'UpTrend Begins', location = location.absolute, style = shape.circle, size = size.tiny, color = color.new(color.green, 0))
plotshape(buySignal and showsignals ? up : na, title = 'Buy', text = 'Buy', location = location.absolute, style = shape.labelup, size = size.tiny, color = color.new(color.green, 0), textcolor = color.new(color.white, 0))
dnPlot = plot(trend == 1 ? na : dn, title = 'Down Trend', style = plot.style_linebr, linewidth = 2, color = color.new(color.red, 0))
sellSignal = trend == -1 and trend == 1
plotshape(sellSignal ? dn : na, title = 'DownTrend Begins', location = location.absolute, style = shape.circle, size = size.tiny, color = color.new(color.red, 0))
plotshape(sellSignal and showsignals ? dn : na, title = 'Sell', text = 'Sell', location = location.absolute, style = shape.labeldown, size = size.tiny, color = color.new(color.red, 0), textcolor = color.new(color.white, 0))
mPlot = plot(ohlc4, title = '', style = plot.style_circles, linewidth = math.max(1, 0))
longFillColor = highlighting ? trend == 1 ? color.green : color.white : color.white
shortFillColor = highlighting ? trend == -1 ? color.red : color.white : color.white
fill(mPlot, upPlot, title = 'UpTrend Highligter', color = longFillColor)
fill(mPlot, dnPlot, title = 'DownTrend Highligter', color = shortFillColor)
alertcondition(buySignal, title = 'SuperTrend Buy', message = 'SuperTrend Buy!')
alertcondition(sellSignal, title = 'SuperTrend Sell', message = 'SuperTrend Sell!')
changeCond = trend != trend
alertcondition(changeCond, title = 'SuperTrend Direction Change', message = 'SuperTrend has changed direction!')
