Predictive Trend and Breaks [PQ_MOD]This PineScript indicator is an advanced predictive tool that combines statistical forecasting with dynamic trend analysis to aid in identifying potential price breakouts. It starts by detecting swing highs and lows over a configurable lookback period and calculates dynamic slopes using methods such as ATR, standard deviation, or linear regression. The script then determines the strongest trend by computing correlations over various periods, automatically selecting the optimal lookback for forecasting. By leveraging an external statistical library, it produces forecasted price levels along with confidence bounds, which are visualized through primary and secondary lines and labels on the chart. Additionally, the indicator draws extended forecast channels and plots breakout markers when prices breach these trendlines, while also offering optional real-time backpainting and a statistical data table. Alert conditions for upward and downward breakouts further enhance its utility for traders monitoring trend reversals.
Regressions
RDMP - StrategyMulti-Indicator Trading Strategy (RSI-Stochastic-Fibonacci-Support/Resistance).
This advanced TradingView indicator combines four powerful technical tools to identify high-probability trading opportunities across all timeframes.
Key Features:
Smart signal system requiring multiple confirmations to reduce false signals
Automatic support/resistance detection with dynamic visualization
Fibonacci retracements calculated on relevant swing points
Trend filter to align with market direction
Timeframe auto-adjustment optimizing parameters for any chart
Visual dashboard displaying all indicator states at a glance
Divergence detection to anticipate potential trend reversals
The indicator overlays key price levels directly on your chart while displaying discrete buy/sell signals when multiple conditions align. Fully customizable parameters allow fine-tuning to your trading style.
Perfect for multi-timeframe traders seeking confirmed entries at key market levels.
Porcentaje sobre/debajo SMAsIdentify strong bullish reversals when:
1) Price spends <30% of time below SMA200 (extreme oversold),
2) Confirmed by RSI<20.
Marcadorde Entradas Long y Short Javier JoseScript Logic
I have integrated the following elements:
Trend Indicators: I use 9-period and 21-period Exponential Moving Averages (EMAs) to quickly detect the price direction.
Momentum Confirmation: I combine the RSI and MACD to validate the strength and direction of the movement.
Volume Filter: I only accept signals if the volume exceeds its 20-period moving average, ensuring market interest.
Volatility Filter: I use the ATR (Average True Range) to avoid signals in flat or low-volatility markets.
Candlestick Patterns: I include detection of engulfing patterns (bullish for "Long," bearish for "Short") as additional confirmation.
Support and Resistance: I use pivot points to ensure signals occur near key levels.
The result is a robust system that filters out weak signals and prioritizes the most reliable ones.
Condition Details
Trend (EMA Crossover)
Long: The fast EMA (9) crosses above the slow EMA (21).
Short: The fast EMA (9) crosses below the slow EMA (21).
Momentum
RSI:
"Long" requires RSI > 40 (avoids extreme oversold zones).
"Short" requires RSI < 60 (avoids extreme overbought zones).
MACD:
"Long" when the MACD line is above the signal line.
"Short" when the MACD line is below the signal line.
Volume
The current volume must exceed the 20-period Simple Moving Average (SMA) of volume.
Volatility (ATR)
The current ATR must exceed its 14-period SMA to ensure sufficient market movement.
Candlestick Patterns
Bullish Engulfing: Confirms "Long" when the current candle closes above the previous candle’s open and engulfs its range.
Bearish Engulfing: Confirms "Short" when the current candle closes below the previous candle’s open and engulfs its range.
Support and Resistance
Support: For "Long," the price must be near (within 1%) a previous low pivot.
Resistance: For "Short," the price must be near (within 1%) a previous high pivot.
Timeframes
The script operates only on the specified timeframes: 15 minutes, 30 minutes, 1 hour, 2 hours, 4 hours, and daily.
Double RSI + MA Signal [AlgoRich]This indicator combines two RSI (Relative Strength Index) indicators with their respective Exponential Moving Averages (EMA) to provide a more detailed view of the market's relative strength.
Its design allows for the identification of overbought and oversold zones, as well as potential trend reversal signals.
How does it work?
1. RSI (Relative Strength Index)
The RSI is an oscillator that measures the speed and change of price movements.
The values range between 0 and 100:
Values above 70 typically indicate overbought conditions (price may be overvalued).
Values below 30 typically indicate oversold conditions (price may be undervalued).
In this indicator, two RSIs are calculated with different periods to capture strength signals in both the short and medium term:
RSI 1: Uses a shorter period (7 by default), making it more sensitive to recent price changes.
RSI 2: Uses a longer period (14 by default), providing a more stable perspective.
2. EMAs (Exponential Moving Averages)
EMAs are calculated for each RSI to smooth their movements:
EMA RSI 1: Smooths RSI 1 (short-term).
EMA RSI 2: Smooths RSI 2 (medium-term).
These EMAs help filter market noise and allow for clearer trend identification in the RSI data.
3. Key Levels
Horizontal reference levels are defined on the chart:
80 (solid red line): Extreme overbought zone.
70 (dotted red line): Initial overbought zone.
50 (dotted gray line): Midline, acting as an equilibrium reference.
30 (dotted green line): Initial oversold zone.
20 (solid green line): Extreme oversold zone.
These levels help interpret market strength:
Above 70: The market is in a strong bullish phase (or overbought).
Below 30: The market is in a strong bearish phase (or oversold).
4. Visualization
The indicator plots:
RSI 1 and its EMA:
RSI 1: Thick green line.
EMA RSI 1: Thin white line that follows RSI 1.
RSI 2 and its EMA:
RSI 2: Thick red line.
EMA RSI 2: Transparent line (not visible in this case but can be enabled if desired).
What is this indicator used for?
1. Identifying Overbought and Oversold Conditions
Levels 70 and 30 indicate zones where the market might be near a trend reversal.
Levels 80 and 20 identify extreme conditions, often accompanied by strong price reversals.
2. Confirming Trends
If the RSI and its EMA are above 50, it indicates a bullish trend.
If the RSI and its EMA are below 50, it indicates a bearish trend.
3. Filtering False Signals
By combining two RSIs with different periods, you can confirm signals more reliably:
If both RSIs are moving in the same direction (above or below 50), the signal is stronger.
EMAs smooth out oscillations, helping to ignore irrelevant short-term movements.
Benefits for Traders
This indicator is useful for:
Scalpers and Day Traders: By using a shorter RSI (RSI 1), you can capture quick movements in the market.
Swing Traders: With the longer RSI (RSI 2), you can identify broader trends.
Risk Management: Avoid trading in extreme overbought/oversold zones (levels 80 and 20).
In summary, this indicator provides a powerful tool to evaluate the market's relative strength, combining multiple analysis timeframes and helping traders make more informed decisions.
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TRADUCCIÓN AL ESPAÑOL:
Explicación del Indicador: Double RSI + MA Signal
Este indicador combina dos RSI (Relative Strength Index) con sus respectivas medias móviles exponenciales (EMA) para proporcionar una visión más detallada de la fuerza relativa del mercado.
Su diseño permite identificar zonas de sobrecompra, sobreventa y posibles señales de cambio de tendencia.
¿Cómo funciona?
1. RSI (Relative Strength Index)
El RSI es un oscilador que mide la velocidad y el cambio en los movimientos de precios.
Los valores oscilan entre 0 y 100:
Valores por encima de 70 suelen indicar sobrecompra (precio posiblemente sobrevalorado).
Valores por debajo de 30 suelen indicar sobreventa (precio posiblemente infravalorado).
En este indicador, se calculan dos RSI con diferentes períodos para capturar señales de fuerza a corto y mediano plazo:
RSI 1: Usando un período más corto (7, por defecto), lo que lo hace más sensible a cambios recientes en el precio.
RSI 2: Usando un período más largo (14, por defecto), proporcionando una visión más estable.
2. EMAs (Exponential Moving Averages)
Se calculan EMAs de cada RSI para suavizar sus movimientos:
EMA RSI 1: Suaviza el RSI 1 (corto plazo).
EMA RSI 2: Suaviza el RSI 2 (mediano plazo).
Estas EMAs ayudan a filtrar el ruido del mercado y permiten identificar tendencias más claras en los datos del RSI.
3. Niveles Clave
Se definen niveles de referencia horizontales en el gráfico:
80 (línea sólida roja): Zona de sobrecompra extrema.
70 (línea punteada roja): Zona inicial de sobrecompra.
50 (línea gris punteada): Línea media, que actúa como una referencia de equilibrio.
30 (línea punteada verde): Zona inicial de sobreventa.
20 (línea sólida verde): Zona de sobreventa extrema.
Estos niveles ayudan a interpretar la fuerza del mercado:
Por encima de 70: El mercado está en una fase alcista fuerte (o sobrecompra).
Por debajo de 30: El mercado está en una fase bajista fuerte (o sobreventa).
4. Visualización
El indicador grafica:
RSI 1 y su EMA:
RSI 1: Línea verde gruesa.
EMA RSI 1: Línea blanca delgada, que sigue al RSI 1.
RSI 2 y su EMA:
RSI 2: Línea roja gruesa.
EMA RSI 2: Línea transparente (no visible en este caso, pero puede activarse si se desea).
¿Para qué sirve este indicador?
1. Identificar sobrecompra y sobreventa
Los niveles de 70 y 30 marcan zonas donde el mercado podría estar cerca de un cambio de tendencia.
Los niveles de 80 y 20 identifican extremos, que suelen estar acompañados de fuertes reversiones de precio.
2. Confirmar tendencias
Si el RSI y su EMA están por encima de 50, indica una tendencia alcista.
Si el RSI y su EMA están por debajo de 50, indica una tendencia bajista.
3. Filtrar señales falsas
Al combinar dos RSI con diferentes períodos, puedes confirmar señales de una forma más confiable:
Si ambos RSI están en la misma dirección (por encima o por debajo de 50), la señal es más fuerte.
Las EMAs suavizan las oscilaciones, ayudando a ignorar movimientos temporales irrelevantes.
Beneficio para los Traders
Este indicador es útil para:
Scalpers y Day Traders: Al usar un RSI más corto (RSI 1), puedes capturar movimientos rápidos en el mercado.
Swing Traders: Con el RSI más largo (RSI 2), puedes identificar tendencias más amplias.
Gestión de riesgos: Evitar operaciones en zonas de sobrecompra/sobreventa extremas (niveles 80 y 20).
En resumen, este indicador proporciona una herramienta poderosa para evaluar la fuerza relativa del mercado, combinando diferentes horizontes de análisis y ayudando a los traders a tomar decisiones informadas.
Futuristic Trend PredictorAI-based trend predictor. converting it to a strategy for backtesting. thanks.
ML Deep Regression Pro (TechnoBlooms)ML Deep Regression Pro is a machine-learning-inspired trading indicator that integrates Polynomial Regression, Linear Regression and Statistical Deviation models to provide a powerful, data-driven approach to market trend analysis.
Designed for traders, quantitative analysts and developers, this tool transforms raw market data into predictive trend insights, allowing for better decision-making and trend validation.
By leveraging statistical regression techniques, ML Deep Regression Pro eliminates market noise and identifies key trend shifts, making it a valuable addition to both manual and algorithmic trading strategies.
REGRESSION ANALYSIS
Regression is a statistical modeling technique used in machine learning and data science to identify patterns and relationships between variables. In trading, it helps detect price trends, reversals and volatility changes by fitting price data into a predictive model.
1. Linear Regression -
The most widely used regression model in trading, providing a best-fit plotted line to track price trends.
2. Polynomial Regression -
A more advanced form of regression that fits curved price structures, capturing complex market cycles and improving trend forecasting accuracy.
3. Standard Deviation Bands -
Based on regression calculations, these bands measure price dispersion and identify overbought/ oversold conditions, similar to Bollinger Bands. By default, these lines are hidden and user can make it visible through Settings.
KEY FEATURES :-
✅ Hybrid Regression Engine – Combines Linear and Polynomial Regression to detect market trends with greater accuracy.
✅ Dynamic Trend Bias Analysis – Identifies bullish & bearish market conditions using real-time regression models.
✅ Standard Deviation Bands – Measures price volatility and potential reversals with an advanced deviation model.
✅ Adaptive EMA Crossover Signals – Generates buy/sell signals when price momentum shifts relative to the regression trend.
[iQ]PRO Ultimate Financial Analysis Tool And System SynergyUltimate Financial Analysis Tool And System Synergy (UFATASS)
Advanced Market Insights with Cycle Analysis, Trend Forecasting, and Risk Monitoring
The Ultimate Financial Analysis Tool And System Synergy (UFATASS) is a powerful indicator designed to give traders a deeper understanding of market dynamics. By blending cutting-edge techniques from signal processing, statistics, and dynamical systems theory, UFATASS provides a unique, all-in-one solution for technical analysis.
Key Features
Cycle Detection:
Pinpoints dominant market cycles using advanced spectral analysis, helping you identify potential turning points.
Trend Analysis:
Delivers multiple regression lines to capture short-term and long-term market trends, with a customizable complexity setting for precision.
Probability Forecasts:
Uses Monte Carlo simulations to estimate the likelihood of future price movements, offering a probabilistic edge for decision-making.
Risk Monitoring:
Tracks volatility and market stability, featuring an experimental chaos indicator based on Lyapunov exponents to assess price predictability.
Customization Options
Adjust the indicator to fit your trading style:
Cycle and regression lookback periods
Complexity factor for regression sensitivity
Volatility calculation window
Forecast horizon for price predictions
Visual Outputs
Price and regression lines plotted on the main chart
Cycle details and wave visuals in a separate pane
A summary label on the last bar with key metrics (e.g., cycle length, probabilities)
Background color alerts to signal risk levels
How to Use
Incorporate UFATASS into your strategy to:
Anticipate reversals with cycle analysis
Confirm trends using regression insights
Plan entries and exits with probability forecasts
Monitor market conditions and adjust risk exposure
Adaptive Trend FinderAdaptive Trend Finder - The Ultimate Trend Detection Tool
Introducing Adaptive Trend Finder, the next evolution of trend analysis on TradingView. This powerful indicator is an enhanced and refined version of Adaptive Trend Finder (Log), designed to offer even greater flexibility, accuracy, and ease of use.
What’s New?
Unlike the previous version, Adaptive Trend Finder allows users to fully configure and adjust settings directly within the indicator menu, eliminating the need to modify chart settings manually. A major improvement is that users no longer need to adjust the chart's logarithmic scale manually in the chart settings; this can now be done directly within the indicator options, ensuring a smoother and more efficient experience. This makes it easier to switch between linear and logarithmic scaling without disrupting the analysis. This provides a seamless user experience where traders can instantly adapt the indicator to their needs without extra steps.
One of the most significant improvements is the complete code overhaul, which now enables simultaneous visualization of both long-term and short-term trend channels without needing to add the indicator twice. This not only improves workflow efficiency but also enhances chart readability by allowing traders to monitor multiple trend perspectives at once.
The interface has been entirely redesigned for a more intuitive user experience. Menus are now clearer, better structured, and offer more customization options, making it easier than ever to fine-tune the indicator to fit any trading strategy.
Key Features & Benefits
Automatic Trend Period Selection: The indicator dynamically identifies and applies the strongest trend period, ensuring optimal trend detection with no manual adjustments required. By analyzing historical price correlations, it selects the most statistically relevant trend duration automatically.
Dual Channel Display: Traders can view both long-term and short-term trend channels simultaneously, offering a broader perspective of market movements. This feature eliminates the need to apply the indicator twice, reducing screen clutter and improving efficiency.
Fully Adjustable Settings: Users can customize trend detection parameters directly within the indicator settings. No more switching chart settings – everything is accessible in one place.
Trend Strength & Confidence Metrics: The indicator calculates and displays a confidence score for each detected trend using Pearson correlation values. This helps traders gauge the reliability of a given trend before making decisions.
Midline & Channel Transparency Options: Users can fine-tune the visibility of trend channels, adjusting transparency levels to fit their personal charting style without overwhelming the price chart.
Annualized Return Calculation: For daily and weekly timeframes, the indicator provides an estimate of the trend’s performance over a year, helping traders evaluate potential long-term profitability.
Logarithmic Adjustment Support: Adaptive Trend Finder is compatible with both logarithmic and linear charts. Traders who analyze assets like cryptocurrencies, where log scaling is common, can enable this feature to refine trend calculations.
Intuitive & User-Friendly Interface: The updated menu structure is designed for ease of use, allowing quick and efficient modifications to settings, reducing the learning curve for new users.
Why is this the Best Trend Indicator?
Adaptive Trend Finder stands out as one of the most advanced trend analysis tools available on TradingView. Unlike conventional trend indicators, which rely on fixed parameters or lagging signals, Adaptive Trend Finder dynamically adjusts its settings based on real-time market conditions. By combining automatic trend detection, dual-channel visualization, real-time performance metrics, and an intuitive user interface, this indicator offers an unparalleled edge in trend identification and trading decision-making.
Traders no longer have to rely on guesswork or manually tweak settings to identify trends. Adaptive Trend Finder does the heavy lifting, ensuring that users are always working with the strongest and most reliable trends. The ability to simultaneously display both short-term and long-term trends allows for a more comprehensive market overview, making it ideal for scalpers, swing traders, and long-term investors alike.
With its state-of-the-art algorithms, fully customizable interface, and professional-grade accuracy, Adaptive Trend Finder is undoubtedly one of the most powerful trend indicators available.
Try it today and experience the future of trend analysis.
This indicator is a technical analysis tool designed to assist traders in identifying trends. It does not guarantee future performance or profitability. Users should conduct their own research and apply proper risk management before making trading decisions.
// Created by Julien Eche - @Julien_Eche
CAPM Alpha & BetaThe CAPM Alpha & Beta indicator is a crucial tool in finance and investment analysis derived from the Capital Asset Pricing Model (CAPM) . It provides insights into an asset's risk-adjusted performance (Alpha) and its relationship to broader market movements (Beta). Here’s a breakdown:
1. How Does It Work?
Alpha:
Definition: Alpha measures the portion of an investment's return that is not explained by market movements, i.e., the excess return over and above what the market is expected to deliver.
Purpose: It represents the value a fund manager or strategy adds (or subtracts) from an investment’s performance, adjusting for market risk.
Calculation:
Alpha is derived from comparing actual returns to expected returns predicted by CAPM:
Alpha = Actual Return − (Risk-Free Rate + β × (Market Return − Risk-Free Rate))
Alpha = Actual Return − (Risk-Free Rate + β × (Market Return − Risk-Free Rate))
Interpretation:
Positive Alpha: The investment outperformed its CAPM prediction (good performance for additional value/risk).
Negative Alpha: The investment underperformed its CAPM prediction.
Beta:
Definition: Beta measures the sensitivity of an asset's returns relative to the overall market's returns. It quantifies systematic risk.
Purpose: Indicates how volatile or correlated an investment is relative to the market benchmark (e.g., S&P 500).
Calculation:
Beta is computed as the ratio of the covariance of the asset and market returns to the variance of the market returns:
β = Covariance (Asset Return, Market Return) / Variance (Market Return)
β = Variance (Market Return) Covariance (Asset Return, Market Return)
Interpretation:
Beta = 1: The asset’s price moves in line with the market.
Beta > 1: The asset is more volatile than the market (higher risk/higher potential reward).
Beta < 1: The asset is less volatile than the market (lower risk/lower reward).
Beta < 0: The asset moves inversely to the market.
2. How to Use It?
Using Alpha:
Portfolio Evaluation: Investors use Alpha to gauge whether a portfolio manager or a strategy has successfully outperformed the market on a risk-adjusted basis.
If Alpha is consistently positive, the portfolio may deliver higher-than-expected returns for the given level of risk.
Stock/Asset Selection: Compare Alpha across multiple securities. Positive Alpha signals that the asset may be a good addition to your portfolio for excess returns.
Adjusting Investment Strategy: If Alpha is negative, reassess the asset's role in the portfolio and refine strategies.
Using Beta:
Risk Management:
A high Beta (e.g., 1.5) indicates higher sensitivity to market movements. Use such assets if you want to take on more risk during bullish market phases or expect higher returns.
A low Beta (e.g., 0.7) indicates stability and is useful in diversifying risk in volatile or bearish markets.
Portfolio Diversification: Combine assets with varying Betas to achieve the desired level of market responsiveness and smooth out portfolio volatility.
Monitoring Systematic Risk: Beta helps identify whether an investment aligns with your risk tolerance. For example, high-Beta stocks may not be suitable for conservative investors.
Practical Application:
Use both Alpha and Beta together:
Assess performance with Alpha (excess returns).
Assess risk exposure with Beta (market sensitivity).
Example: A stock with a Beta of 1.2 and a highly positive Alpha might suggest a solid performer that is slightly more volatile than the market, making it a suitable pick for risk-tolerant, return-maximizing investors.
In conclusion, the CAPM Alpha & Beta indicator gives a comprehensive view of an asset's performance and risk. Alpha enables performance evaluation on a risk-adjusted basis, while Beta reveals the level of market risk. Together, they help investors make informed decisions, build optimal portfolios, and align investments with their risk-return preferences.
Simple APF Strategy Backtesting [The Quant Science]Simple backtesting strategy for the quantitative indicator Autocorrelation Price Forecasting. This is a Buy & Sell strategy that operates exclusively with long orders. It opens long positions and generates profit based on the future price forecast provided by the indicator. It's particularly suitable for trend-following trading strategies or directional markets with an established trend.
Main functions
1. Cycle Detection: Utilize autocorrelation to identify repetitive market behaviors and cycles.
2. Forecasting for Backtesting: Simulate trades and assess the profitability of various strategies based on future price predictions.
Logic
The strategy works as follow:
Entry Condition: Go long if the hypothetical gain exceeds the threshold gain (configurable by user interface).
Position Management: Sets a take-profit level based on the future price.
Position Sizing: Automatically calculates the order size as a percentage of the equity.
No Stop-Loss: this strategy doesn't includes any stop loss.
Example Use Case
A trader analyzes a dayli period using 7 historical bars for autocorrelation.
Sets a threshold gain of 20 points using a 5% of the equity for each trade.
Evaluates the effectiveness of a long-only strategy in this period to assess its profitability and risk-adjusted performance.
User Interface
Length: Set the length of the data used in the autocorrelation price forecasting model.
Thresold Gain: Minimum value to be considered for opening trades based on future price forecast.
Order Size: percentage size of the equity used for each single trade.
Strategy Limit
This strategy does not use a stop loss. If the price continues to drop and the future price forecast is incorrect, the trader may incur a loss or have their capital locked in the losing trade.
Disclaimer!
This is a simple template. Use the code as a starting point rather than a finished solution. The script does not include important parameters, so use it solely for educational purposes or as a boilerplate.
Ethereum Logarithmic Regression Bands (Fine-Tuned)This indicator, "Ethereum Logarithmic Regression Bands (Fine-Tuned)," is my attempt to create a tool for estimating long-term trends in Ethereum (ETH/USD) price action using logarithmic regression bands. Please note that I am not an expert in financial modeling or coding—I developed this as a personal project to serve as a rough estimation rather than a precise or professional trading tool. The data was fitted to non-bubble periods of Ethereum's history to provide a general trendline, but it’s far from perfect.
I’m sharing this because I couldn’t find a similar indicator available, and I thought it might be useful for others who are also exploring ETH’s long-term behavior. The bands start from Ethereum’s launch price and are adjustable via input parameters, but they are based on my best effort to align with historical data. With some decent coding experience, I’m sure someone could refine this further—perhaps by optimizing the coefficients or incorporating more advanced fitting techniques. Feel free to tweak the code, suggest improvements, or use it as a starting point for your own projects!
How to Use:
** THIS CHART IS SPECIFICALLY CODED FOR ETH/USD (KRAKEN) ON THE WEEKLY TIMEFRAME IN LOG VIEW**
The main band (blue) represents the logarithmic regression line.
The upper (red) and lower (green) bands provide a range around the main trend, adjustable with multipliers.
Adjust the "Launch Price," "Base Coefficient," "Growth Coefficient," and other inputs to experiment with different fits.
Disclaimer:
This is not financial advice. Use at your own risk, and always conduct your own research before making trading decisions.
NeoTrend AI- Advanced Trading SignalsNeoTrend AI – Advanced Trading Signals
Overview
NeoTrend AI is an advanced trading signal indicator that uniquely integrates a kernel-based predictive model with adaptive volatility analysis. By processing historical price data through a Gaussian kernel matrix, NeoTrend AI produces a statistically informed predicted price. This prediction is then used to generate dynamic volatility bands that serve as adaptive support and resistance levels, leading to clear BUY and SELL signals.
Originality and Usefulness
Innovative Mashup: NeoTrend AI isn’t a mere combination of common indicators; it fuses a novel kernel-based forecasting method with volatility analysis. This creates a tool that not only tracks trends but also identifies key market zones with enhanced precision.
Actionable Insights: The indicator’s design helps traders understand both the underlying trend and the market’s volatility, providing a robust framework for making informed trading decisions.
Customizable Approach: With user-adjustable settings for lookback periods, prediction offsets, smoothness factors, and volatility multipliers, NeoTrend AI adapts to various markets and trading styles.
Omissions and Realistic Claims
Transparent Methodology: NeoTrend AI’s signals are generated solely from historical data analysis using well-established mathematical techniques. There are no unrealistic promises—past performance does not guarantee future results.
No Unsubstantiated Claims: All performance metrics and signal accuracy are clearly derived from the underlying methodology. This script is designed to provide useful insights rather than definitive trading outcomes.
Strategy Results
Kernel Forecasting:
The script builds a Gaussian kernel matrix over a chosen lookback period, smoothing historical price data and generating a predictive price that adjusts dynamically.
Adaptive Volatility Bands:
A volatility band is calculated based on the difference between the actual price and the predicted price, scaled by a user-defined multiplier. These bands change in real time, acting as dynamic support and resistance levels.
Signal Generation:
BUY Signal: Issued when the current price moves above the upper volatility band and the predicted price is trending upward.
SELL Signal: Issued when the price falls below the lower volatility band while the predicted price is trending downward.
Visual Examples
Buy and sell signals are generated, as clearly shown on the chart
Usage Tips
Parameter Customization: Adjust the lookback period, smoothness factor, and volatility multiplier to fit your trading timeframe and market conditions.
Combine with Other Tools: Use NeoTrend AI alongside additional technical indicators and robust risk management strategies for best results.
Backtest Thoroughly: Always perform comprehensive backtesting to understand how the indicator behaves under different market scenarios.
Final Remarks
NeoTrend AI is built to offer traders an original, data-driven insight into market trends without resorting to exaggerated or misleading claims. Its design emphasizes both innovation and practicality, ensuring that you receive actionable signals based on sound statistical methods.
PRC-EPMA | QuantEdgeB Introducing PRC-EPMA by QuantEdgeB
Overview
The PRC-EPMA (Percentile-Endpoint Moving Average) is a sophisticated trading indicator developed for traders looking to capitalize on trend shifts with enhanced filtering mechanisms. It blends Endpoint Moving Averages, Percentile Rank, and Median Absolute Deviation (MAD) Filtering to generate high-probability long and short signals.
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Key Features
🔹 1. Endpoint Moving Average (EPMA):
- A regression-based moving average that adapts quickly to price movements.
- Uses a linear regression slope to project future price direction.
- Helps traders identify trend direction more responsively than traditional moving averages.
🔹 2. Percentile Rank-Based Dynamic Levels:
- Identifies overbought (75th percentile) and oversold (25th percentile) zones.
- Dynamically adjusts based on historical data, making it robust across different market conditions.
🔹 3. Median Absolute Deviation (MAD) Filtering:
- An advanced volatility filter that refines entry and exit points.
- Reduces noise by filtering out weak signals, focusing only on meaningful trend shifts.
- Uses two multipliers (long and short) to fine-tune sensitivity.
🔹 4. Signal Generation:
- 📈Long Signal: Triggered when price closes above the upper dynamic threshold.
- 📉Short Signal: Triggered when price closes below the lower dynamic threshold.
- Uses color-coded candles to visually indicate trend shifts.
- Optional signal labels can be enabled for clear entry/exit indications.
🔹 5. Customizable Visualization:
- Multiple color themes to match user preferences.
- Ability to overlay signals on price charts.
- Alerts available for long & short crossovers.
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How It Works
1. The script calculates an Endpoint Moving Average based on a user-defined period.
2. It computes the 75th and 25th percentile ranks of the Endpoint Moving Average.
3. Median Absolute Deviation (MAD) Filtering is applied to reduce false breakouts.
4. A buy (long) or sell (short) signal is triggered when price crosses the respective filtered percentile levels.
5. Alerts and labels can be used to notify traders of new signals.
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Behavior across Crypto Majors (Using Default Settings)
BTC
ETH
SOL
Note : Past behaviour is not indicative of future results. Always conduct thorough testing and risk management before making trading decisions.
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Best Use Cases
📌 Trend Confirmation – Use EPMA to confirm if a trend is strengthening or weakening.
📌 Noise Reduction – MAD filtering prevents reacting to minor fluctuations, focusing on stronger trend shifts.
📌 Multi-Timeframe Scalability – Works across multiple timeframes (1H, 4H, Daily, etc.), depending on the trader’s strategy.
⚙️ Customizable Inputs ⚙️
- Endpoint Moving Average Lookback Length
- Percentile Rank Length
- MAD Filter Sensitivity (Multipliers for Long & Short)
- Signal Labels & Alerts for Long/Short Entries
- Color Theme Selection
Default Setup for PRC-EPMA
Linear Regression Length → 4
Endpoint Lookback → 14
Percentile Length → 21
Median Period (Absolute Deviation Filter) → 21
Upper Multiplier (Absolute Deviation Filter) → 1.8
Lower Multiplier (Absolute Deviation Filter) → 0.9
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Final Thoughts
The PRC-EPMA Indicator is a powerful tool for traders seeking high-quality entry and exit signals based on statistical and regression-based methodologies. By combining EPMA, Percentile Rank, and MAD Filtering, it ensures that only strong and validated signals are executed, making it a great addition for trend-followers and mean-reversion traders alike.
🔹 Disclaimer: Past performance is not indicative of future results. No trading strategy can guarantee success in financial markets.
🔹 Strategic Advice: Always backtest, optimize, and align parameters with your trading objectives and risk tolerance before live trading.
ICT Session by LasinsName: ICT Session by Lasins
Purpose: To visually identify and differentiate between the Asian, London, and New York trading sessions on the chart.
Features:
Highlights the background of the chart during each session.
Includes a mini dashboard in the top-right corner to show the active session.
Allows customization of time zones (exchange timezone or UTC).
Displays copyright and author information.
Key Components
Inputs:
useExchangeTimezone: A boolean input to toggle between using the exchange timezone or UTC for session times.
showDashboard: A boolean input to toggle the visibility of the mini dashboard.
Session Times:
The script defines three trading sessions:
Asian Session: 2000-0000 UTC (or adjusted for exchange timezone).
London Session: 0200-0500 UTC (or adjusted for exchange timezone).
New York Session: 0700-1000 UTC (or adjusted for exchange timezone).
Session Detection:
The is_session function checks if the current time falls within a specified session using the time function.
Background Coloring:
The bgcolor function is used to highlight the chart background during each session:
Asian Session: Red background.
London Session: Green background.
New York Session: Blue background.
Mini Dashboard:
A table is created in the top-right corner of the chart to display the active session and its corresponding color.
The dashboard includes:
A header row with "Session" and "Color".
Rows for each session (Asian, London, New York) with their respective colors.
Copyright and Author Information:
A label is added to the chart to display the copyright and author information ("© ICT Session by Lasins Raj").
How It Works
The script checks the current time and compares it to the predefined session times.
If the current time falls within a session, the chart background is highlighted with the corresponding color.
The mini dashboard updates to reflect the active session.
The copyright and author information is displayed at the bottom of the chart.
Customization
You can adjust the session times in the script to match your preferred timezone or trading hours.
The useExchangeTimezone input allows you to switch between UTC and the exchange timezone.
The showDashboard input lets you toggle the visibility of the mini dashboard.
Example Use Case
Traders who follow the ICT (Inner Circle Trader) methodology can use this indicator to identify key trading sessions and plan their trades accordingly.
The visual representation of sessions helps traders quickly recognize when major markets are open and active.
TASC 2025.03 A New Solution, Removing Moving Average Lag█ OVERVIEW
This script implements a novel technique for removing lag from a moving average, as introduced by John Ehlers in the "A New Solution, Removing Moving Average Lag" article featured in the March 2025 edition of TASC's Traders' Tips .
█ CONCEPTS
In his article, Ehlers explains that the average price in a time series represents a statistical estimate for a block of price values, where the estimate is positioned at the block's center on the time axis. In the case of a simple moving average (SMA), the calculation moves the analyzed block along the time axis and computes an average after each new sample. Because the average's position is at the center of each block, the SMA inherently lags behind price changes by half the data length.
As a solution to removing moving average lag, Ehlers proposes a new projected moving average (PMA) . The PMA smooths price data while maintaining responsiveness by calculating a projection of the average using the data's linear regression slope.
The slope of linear regression on a block of financial time series data can be expressed as the covariance between prices and sample points divided by the variance of the sample points. Ehlers derives the PMA by adding this slope across half the data length to the SMA, creating a first-order prediction that substantially reduces lag:
PMA = SMA + Slope * Length / 2
In addition, the article includes methods for calculating predictions of the PMA and the slope based on second-order and fourth-order differences. The formulas for these predictions are as follows:
PredictPMA = PMA + 0.5 * (Slope - Slope ) * Length
PredictSlope = 1.5 * Slope - 0.5 * Slope
Ehlers suggests that crossings between the predictions and the original values can help traders identify timely buy and sell signals.
█ USAGE
This indicator displays the SMA, PMA, and PMA prediction for a specified series in the main chart pane, and it shows the linear regression slope and prediction in a separate pane. Analyzing the difference between the PMA and SMA can help to identify trends. The differences between PMA or slope and its corresponding prediction can indicate turning points and potential trade opportunities.
The SMA plot uses the chart's foreground color, and the PMA and slope plots are blue by default. The plots of the predictions have a green or red hue to signify direction. Additionally, the indicator fills the space between the SMA and PMA with a green or red color gradient based on their differences:
Users can customize the source series, data length, and plot colors via the inputs in the "Settings/Inputs" tab.
█ NOTES FOR Pine Script® CODERS
The article's code implementation uses a loop to calculate all necessary sums for the slope and SMA calculations. Ported into Pine, the implementation is as follows:
pma(float src, int length) =>
float PMA = 0., float SMA = 0., float Slope = 0.
float Sx = 0.0 , float Sy = 0.0
float Sxx = 0.0 , float Syy = 0.0 , float Sxy = 0.0
for count = 1 to length
float src1 = src
Sx += count
Sy += src
Sxx += count * count
Syy += src1 * src1
Sxy += count * src1
Slope := -(length * Sxy - Sx * Sy) / (length * Sxx - Sx * Sx)
SMA := Sy / length
PMA := SMA + Slope * length / 2
However, loops in Pine can be computationally expensive, and the above loop's runtime scales directly with the specified length. Fortunately, Pine's built-in functions often eliminate the need for loops. This indicator implements the following function, which simplifies the process by using the ta.linreg() and ta.sma() functions to calculate equivalent slope and SMA values efficiently:
pma(float src, int length) =>
float Slope = ta.linreg(src, length, 0) - ta.linreg(src, length, 1)
float SMA = ta.sma(src, length)
float PMA = SMA + Slope * length * 0.5
To learn more about loop elimination in Pine, refer to this section of the User Manual's Profiling and optimization page.
UM-Optimized Linear Regression ChannelDESCRIPTION
This indicator was inspired by Dr. Stoxx at drstoxx.com. Shout out to him and his services for introducing me to this idea. This indicator is a slightly different take on the standard linear regression indicator.
It uses two standard deviations to draw bands and dynamically attempts to best-fit the data lookback period using an R-squared statistical measure. The R-squared value ranges between zero and one with zero being no fit to the data at all and 1 being a 100% match of the data to linear regression line. The R-squared calculation is weighted exponentially to give more weight to the most recent data.
The label provides the number of periods identified as the optimal best-fit period, the type of loopback period determination (Manual or Auto) and the R-squared value (0-100, 100% being a perfect fit). >=90% is a great fit of the data to the regression line. <50% is a difficult fit and more or less considered random data.
The lookback mode can also be set manually and defaults to a value of 100 periods.
DEFAULTS
The defaults are 1.5 and 2.0 for standard deviation. This creates 2 bands above and below the regression line. The default mode for best-fit determination with "Auto" selected in the dropdown. When manual mode is selected, the default is 100. The modes, manual lookback periods, colors, and standard deviations are user-configurable.
HOW TO USE
Overlay this indicator on any chart of any timeframe. Look for turning points at extremes in the upper and lower bands. Look for crossovers of the centerline. Look at the Auto-determination for best fit. Compare this to your favorite Manual mode setting (Manual Mode is set to 100 by default lookback periods.)
When price is at an extreme, look for turnarounds or reversals. Use your favorite indicators, in addition to this indicator, to determine reversals. Try this indicator against your favorite securities and timeframes.
CHART EXAMPLE
The chart I used for an example is the daily chart of IWM. I illustrated the extremes with white text. This is where I consider proactively exiting an existing position and/or begin looking for a reversal.
CandelaCharts - Fib Retracement (OTE) 📝 Overview
The CandelaCharts Fib Retracement (OTE) indicator is a precision tool designed to help traders identify Optimal Trade Entry (OTE) levels based on Fibonacci retracement principles, as taught in ICT (Inner Circle Trader) methodology.
This indicator automatically plots Fibonacci retracement levels between a selected swing high and swing low, highlighting the key OTE zone between the 61.8% and 78.6% retracement levels—a prime area for potential reversals in trending markets.
📦 Features
Automatic & Custom lookback modes
Customizable fib levels
Dynamic coloring
Reverse & extend
⚙️ Settings
Lookback: Controls the number of bars to look back. You can choose between **Automatic** or **Custom** mode.
Line Style: Sets the line style for the Fibonacci levels.
Levels: 0, 0.236, 0.0.382, 0.500, 0.620, 0.705, 0.790, 0.886, 1.000. Allows you to toggle the visibility of Fibonacci levels.
Dynamic Coloring: Colors Fibonacci levels according to trend direction.
Show Labels: Shows the price value at each Fibonacci level.
Reverse: Flips the Fibonacci levels in the opposite direction.
Extend Left: Extends the Fibonacci levels to the left.
⚡️ Showcase
Dynamic Coloring
Manual Coloring
Fib Retracement
Extended
Custom Length
📒 Usage
Using the CandelaCharts Fib Retracement (OTE) is pretty straightforward—just follow these steps to spot high-probability trade setups and refine your entries.
Identify the Trend – Determine whether the market is in an uptrend or downtrend.
Select Swing Points – The indicator automatically plots from the most recent swing high to swing low (or vice versa).
Wait for Price to Enter OTE Zone – Look for price action confirmation within the optimal entry zone (61.8%-78.6%).
Enter the Trade – Consider longs in an uptrend at the OTE zone, and shorts in a downtrend.
Set Stop & Target – Place stops below/above the swing low/high and target extension levels (127.2%, 161.8%).
🎯 Key takeways
The CandelaCharts Fib Retracement (OTE) is a must-have tool for traders looking to refine their entries and maximize risk-reward potential with precision-based ICT trading strategies. 🚀
🚨 Alerts
The indicator does not provide any alerts!
⚠️ Disclaimer
Trading involves significant risk, and many participants may incur losses. The content on this site is not intended as financial advice and should not be interpreted as such. Decisions to buy, sell, hold, or trade securities, commodities, or other financial instruments carry inherent risks and are best made with guidance from qualified financial professionals. Past performance is not indicative of future results.
MOKI V1The "MOKI V1" script is a trading strategy on the TradingView platform that uses a combination of two key indicators to identify buy and sell signals:
EMA200 (Exponential Moving Average 200): Used to determine the overall market trend. This line helps ensure that trades are made in the direction of the primary market trend.
RSI (Relative Strength Index): Used to measure the strength or weakness of a trend. In this strategy, a reading above 50 for the RSI indicates stronger buy signals.
Engulfing Pattern: This candlestick pattern occurs when a green (bullish) candle completely engulfs the previous red (bearish) candle. It is used as a buy signal when combined with the other indicators.
BIAS PRO - Zones + Liquidity + SP&RS [AlgoRich]This multifunction indicator is used to identify key areas on the chart, liquidity levels, and support/resistance zones (SP&RS). Its design is aimed at highlighting price pivots (swings) by drawing zones (boxes and lines) based on these pivots, while also displaying information about trading sessions and levels of analysis across different timeframes.
1. Configuration and Input Parameters
Swing Parameters (Bars Right-Left):
Two inputs are defined to adjust the number of bars on the right and left used to detect pivots (swings). This allows the determination of high and low pivot points.
Display Options:
You can choose to show or hide boxes, lines, and labels (bubbles). There is also an option to extend the zones until they are “filled” (confirmed), and you can opt to hide those zones once filled.
Appearance:
Visual parameters are defined, such as the option to display high and low pivots, colors for lines, labels, and boxes (for both bullish and bearish conditions), line styles (solid, dotted, dashed), and other aesthetic details (box width, label size, text alignment).
Lookback and Time Range:
The “lookback” and “daysBack” variables determine whether the analysis is limited to data from a certain number of days, helping to filter out older historical information.
2. Calculation of Pivots (Swings) and Zone Detection
Price Pivots:
Using the pivot functions (ta.pivothigh and ta.pivotlow), the script identifies swing high and low points based on the configured swing size (bars left and right).
If a swing high is detected, its bar index is stored and the corresponding signal is activated.
Similarly, a swing low is detected and marked.
Drawing Zones:
When a swing (high or low) is detected and the time range condition is met (inRange), the script draws:
Boxes: These visually represent the area around the pivot level. The configuration (type and width) is adjustable.
Lines: A horizontal line is drawn from the pivot point to the current bar, using the defined style and color.
Boxes and lines are drawn for both high pivots (showhighs) and low pivots (showlows).
Additionally, these zones are updated and extended dynamically as new bars appear, and zones that are “filled” (when the price exceeds the zone level) are removed.
Labels and Markers:
If enabled, the script displays circle markers (using plotshape) at the swing points.
3. Operational Zone (Sessions)
Customizable Sessions:
The script allows defining up to three operational sessions with distinct time ranges and colors.
For example, Session 1, Session 2, and Session 3 have configurable time ranges and colors (with adjustable opacity).
It checks if the current time falls within any of these sessions and, if so, applies a background color (bgcolor) to the chart with the configured session color.
Timezone Adjustment:
You can configure a UTC offset or use the exchange’s timezone to correctly adjust the session times.
4. Additional Levels and Analysis Groups
Groups of Levels (Levels 1, 2, 3, and 4):
Several groups are defined that allow data requests from different timeframes (e.g., 60 minutes, 240 minutes, daily, or weekly) and configure their parameters (length, line style, color).
For each group, the script uses a function that requests non-repainting data and calculates pivot levels based on ta.pivothigh/ta.pivotlow.
These levels are drawn on the chart with lines and “shadow” lines to reinforce the visualization of key pivot points. Labels are added with a slight offset to indicate the pivot value in the corresponding timeframe.
5. Maintenance and Management of Drawn Elements
Dynamic Update and Deletion:
The script maintains arrays to store the drawn boxes and lines. As new elements are added and the array reaches a maximum size (e.g., 500 elements), the oldest elements are deleted to avoid overloading the chart.
Extension and Hiding Conditions:
Conditions are checked to extend or delete zones based on whether the price has “filled” the area (i.e., if the current price has surpassed the zone level). There is also an option to hide zones once they are filled.
6. Session (Operational Zone) and Levels for Multiple Timeframes
Session Settings:
In addition to the pivot zones, the indicator also defines operational sessions with adjustable time ranges and colors, shading the background of the chart during those sessions.
Additional Level Groups:
The indicator allows grouping of analysis levels by timeframe, which can be useful for multi-timeframe analysis. Parameters such as length, style, and color are configurable for each group.
Summary:
The "BIAS PRO - Zones + Liquidity + SP&RS " is an all-in-one indicator that combines the detection of price pivots (swings) with the visual representation of key zones on the chart. With options to customize appearance, manage operational sessions, and group levels across different timeframes, this script is designed to help traders identify areas of high liquidity, potential breakouts, or reversals, thus optimizing decision-making based on market structure.
This explanation covers the main functionalities and workflow of the script, making it easier to understand without needing to examine the code in detail.
Pearson Correlation CoefficientDescription: The Pearson Correlation Coefficient measures the strength and direction of the linear relationship between two data series. Its value ranges from -1 to +1, where:
+1 indicates a perfect positive linear correlation: as one asset increases, the other asset increases proportionally.
0 indicates no linear correlation: variations in one asset have no relation to variations in the other asset.
-1 indicates a perfect negative linear correlation: as one asset increases, the other asset decreases proportionally.
This measure is widely used in technical analysis to assess the degree of correlation between two financial assets. The "Pearson Correlation (Manual Compare)" indicator allows users to manually select two assets and visually display their correlation relationship on a chart.
Features:
Correlation Period: The time period used for calculating the correlation can be adjusted (default: 50).
Comparison Asset: Users can select a secondary asset for comparison.
Visual Plots: The chart includes reference lines for perfect correlations (+1 and -1) and strong correlations (+0.7 and -0.7).
Alerts: Set alerts for when the correlation exceeds certain threshold values (e.g., +0.7 for strong positive correlation).
How to Select the Second Asset:
Primary Asset Selection: The primary asset is the one you select for viewing on the chart. This can be done by simply opening the chart for the desired asset.
Secondary Asset Selection: To select the secondary asset for comparison, use the input field labeled "Comparison Asset" in the script settings. You can manually enter the ticker symbol of the secondary asset you want to compare with the primary asset.
This indicator is ideal for traders looking to identify relationships and correlations between different financial assets to make informed trading decisions.
Statistical Arbitrage Pairs Trading - Long-Side OnlyThis strategy implements a simplified statistical arbitrage (" stat arb ") approach focused on mean reversion between two correlated instruments. It identifies opportunities where the spread between their normalized price series (Z-scores) deviates significantly from historical norms, then executes long-only trades anticipating reversion to the mean.
Key Mechanics:
1. Spread Calculation: The strategy computes Z-scores for both instruments to normalize price movements, then tracks the spread between these Z-scores.
2. Modified Z-Score: Uses a robust measure combining the median and Median Absolute Deviation (MAD) to reduce outlier sensitivity.
3. Entry Signal: A long position is triggered when the spread’s modified Z-score falls below a user-defined threshold (e.g., -1.0), indicating extreme undervaluation of the main instrument relative to its pair.
4. Exit Signal: The position closes automatically when the spread reverts to its historical mean (Z-score ≥ 0).
Risk management:
Trades are sized as a percentage of equity (default: 10%).
Includes commissions and slippage for realistic backtesting.
VFV Correction Levels
This Pine Script, "VFV Correction Levels," identifies significant daily price corrections and calculates corresponding investments based on fixed thresholds (paliers). Key features include:
Six predefined correction levels trigger investments between $150 and $600 based on the percentage drop.
Larger corrections correspond to higher investment amounts.
Graphical Indicators:
Visual labels mark correction levels and display investment amounts directly on the chart.
Investment Tracking:
Calculates total invested and tracks performance (yield percentage) relative to the initial correction price.
