Kairos StrategyKairos meaning: The right or critical moment
Overview
Kairos Strategy combines multiple technical indicators and filters to create a robust framework for identifying, confirming, and managing trade entries in both trending and ranging markets. The strategy's core revolves around Hull Moving Average (HMA) variants for primary trend detection, supported by VWMA, SMMA, and ZLSMA for precision in signal confirmation. The integration of Parabolic SAR, ATR-based Stop Loss, and RSI filters ensures accurate entry points and risk control. This multi-layered approach provides flexibility and reliability across timeframes and market conditions.
Methodology
The Kairos Strategy employs a systematic approach to analyze market dynamics:
Primary Trend Identification
The Hull Moving Average (HMA) and its variants (THMA and EHMA) detect major trends.
Users can adjust sources like VWMA, SMMA, and ZLSMA for improved accuracy and trend clarity.
Multi-Indicator Integration
Parabolic SAR signals align with price direction to identify actionable trade zones.
RSI Filters ensure trades occur during optimal momentum conditions, avoiding overbought/oversold areas.
Dynamic Risk Management
ATR-based Stop Loss adapts to volatility, ensuring proper risk/reward ratios.
A customizable trailing stop follows price movements, locking profits while minimizing risk.
Signal Filtering
To enhance reliability, entries are validated by avoiding conditions where price interacts directly with the moving averages.
Customization and Flexibility
The Kairos Strategy empowers traders to adapt to different trading styles and market environments through an array of customizable settings. Each component of the strategy is fine-tuned for flexibility and precision, ensuring it meets the diverse needs of its users.
Configurable Indicators and Sources
Select from multiple moving average options, including LSMA, VWMA, SMMA, VAMA, and ZLSMA, for trend identification and crossover signals.
Adjust the length, smoothing type, and multiplier settings for each indicator to suit various market conditions and timeframes.
Incorporate higher timeframes for broader trend validation without sacrificing detail on lower timeframes.
Risk-Reward Optimization
Define distinct risk-reward ratios for both long and short trades, allowing for tailored approaches to each market scenario.
Enable ATR-based stop-loss calculations for adaptive risk management that responds to market volatility.
Utilize bar-based stop-loss levels for simpler, price-action-driven risk placement.
Strategy Logic
The Kairos Strategy's multi-layered logic is designed to maximize trading opportunities while minimizing false signals:
Entry Conditions
Crossover Signals: The strategy identifies buy or sell signals when a selected moving average crosses over the Hull MA in the direction of the trend.
Momentum Validation: RSI filters ensure that entries are aligned with favorable momentum conditions, reducing exposure to false signals during choppy markets.
Trend Alignment: Parabolic SAR confirms that entries align with the current price trend, adding an additional layer of validation.
Price Interaction Check: The strategy avoids signals when price touches key levels, such as the moving averages or crossover sources, ensuring cleaner entries.
Exit Conditions
Stop-Loss Placement: Choose between ATR-based or bar-based stop-loss calculations, ensuring exits are optimized for risk control.
Take-Profit Targets: Automatically calculated based on customizable risk-reward ratios, providing a consistent framework for locking in gains.
Trailing Stops: Optional trailing stops dynamically adjust with price movement, preserving profits as trends evolve.
Key Benefits
Versatility Across Markets: Effective in both trending and ranging conditions, with settings adaptable to any trading style.
Enhanced Signal Accuracy: Multi-indicator validation and dynamic filtering reduce noise and improve entry timing.
Robust Risk Management: Advanced stop-loss and risk-reward configurations safeguard capital while optimizing trade potential.
User-Friendly Interface: Intuitive settings and customizable visuals make the strategy accessible to both novice and experienced traders.
Use Cases
Trend Trading: Utilize the Hull MA and its variants to capture long-term trends with precision and confidence.
Scalping: Leverage shorter timeframes and the strategy's adaptive indicators for quick, high-frequency trades.
Swing Trading: Combine multi-timeframe analysis and dynamic stop-loss settings to capture medium-term market moves.
Backtest Results
Symbol: BTCUSDT.P Bitcoin / TetherUS PREPERTUAL CONTRACT Binance
Timeframe: 1h
Operating window: Date range of backtests is 2022.01.08 - 2024.11.26. It is chosen to let the strategy to close all opened positions.
Commission and Slippage: Includes a standard Binance commission of 0.07% and accounts for possible slippage over 5 ticks.
Initial capital: 1000 USDT
Percent of capital used in every trade: 100 USDT on 30x leverage = 3000 USDT
Maximum Single Profit: 463.95 USDT
Maximum Single Position Loss: 219.34 USDT
Net Profit: +7,302.60 USDT (730.26%)
Total Trades: 156 (52.56% Win rate)
Profit Factor: 2.443
Maximum Drawdown: 640.29 USDT (-29.65%)
Average Profit per Trade: 46.81 USDT (+1.56%)
I recommend this strategy for leverage trading, that's why the trading properties are set this way!
Disclaimer
This tool is designed for educational and informational purposes, reflecting Kairos dedication to empowering traders with knowledge. Keep in mind that past performance is not indicative of future results. Always test strategies in a simulated environment before applying them in live markets.
Media Mobile di Hull (HMA)
Trend Flow Line (TFL)The Trend Flow Line (TFL) is a versatile moving average indicator that dynamically adjusts to trends using a combination of Hull and Weighted Moving Averages, with optional color coding for bullish and bearish trends.
Introduction
The Trend Flow Line (TFL) is a powerful indicator designed to help traders identify and follow market trends with precision. It combines multiple moving average techniques to create a responsive yet smooth trendline. Whether you're a beginner or an experienced trader, the TFL can enhance your chart analysis by highlighting key price movements and trends.
Detailed Description
The Trend Flow Line (TFL) goes beyond traditional moving averages by leveraging a hybrid approach to calculate trends.
Here's how it works:
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Combination of Hull and Weighted Moving Averages
The TFL integrates the Hull Moving Average (HMA), known for its fast responsiveness, and the Double Weighted Moving Average (DWMA), which offers smooth transitions.
The HMA is adjusted dynamically based on the user-defined length, ensuring adaptability to various trading styles and timeframes.
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Dynamic Smoothing
The TFL calculates its value by averaging the HMA and DWMA, creating a balanced line that responds to market fluctuations without excessive noise.
This balance makes it ideal for identifying both short-term reversals and long-term trends.
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Customizable Features
Timeframe: Analyze the indicator on custom timeframes, independent of the chart's current timeframe.
Color Coding: Optional color settings visually differentiate bullish (uptrend) and bearish (downtrend) phases.
Line Width: Adjust the line thickness to suit your chart preferences.
Color Smoothness: Fine-tune how quickly the color changes to reflect trend shifts, providing a visual cue for potential reversals.
The TFL's algorithm ensures a blend of precision and adaptability, making it suitable for any market or trading strategy.
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The Trend Flow Line (TFL) is an essential tool for traders looking to stay ahead of market trends while maintaining a clear and visually intuitive charting experience. It combines HMA and DWMA for trend sensitivity and smoothness.
HMA w(LRLR)Description: This script combines a customizable Hull Moving Average (HMA) with a Low Resistance Liquidity Run (LRLR) detection system, ideal for identifying trend direction and potential breakout points in a single overlay.
Features:
Hull Moving Average (HMA):
Select separate calculation sources (open, high, low, close) for short and long periods.
Choose from SMA, EMA, and VWMA for length type on both short and long periods, offering flexible moving average calculations to suit different trading strategies.
Color-coded HMA line that visually changes based on crossover direction, providing an intuitive view of market trends.
Customizable options for line thickness, color transparency, and band fill between HMA short and long lines.
Low Resistance Liquidity Run (LRLR):
Detects breakout signals based on price and volume conditions, identifying potential liquidity run levels.
User-defined length and breakout multiplier control breakout sensitivity and adjust standard deviation-based thresholds.
Color-coded visual markers for bullish and bearish LRLR signals, customizable for user preference.
Alerts for both bullish and bearish LRLR events, keeping users informed of potential trading opportunities.
This script allows traders to visually track the HMA trend direction while also spotting low-resistance liquidity opportunities, all on one chart overlay.
Disclaimer: This tool is intended for educational purposes only and should not be used solely to make trading decisions. Adjust parameters as needed, and consider additional analysis for comprehensive decision-making.
Rolling Reversion BandsRolling Reversion Bands: A Technical Trading Indicator
This indicator helps traders spot potential reversal opportunities by showing where price might be overextended and likely to return to average levels. It combines two powerful technical tools - Volume Weighted Average Price (VWAP) and Hull Moving Average (HMA) smoothing - to create a more reliable signal.
Key Features:
Golden centerline: A smoothed VWAP that filters out market noise
Uses volume-weighted pricing for better accuracy than simple averages
HMA smoothing reduces false signals while staying responsive to real moves
Works like a "fair value" level that price tends to return to
Colored bands:
Turquoise bands (#32f0dd): Show shorter-term price ranges (100 periods)
Pink/red bands (#c2024f): Show longer-term price ranges (200 periods)
Two levels for each color (inner and outer bands)
How to Use It:
When price moves outside the bands, it might be overextended
The golden HMA-smoothed VWAP centerline acts as a target level where price often returns to
Wider bands show higher volatility, narrower bands show lower volatility
You can toggle different bands on/off to keep your chart clean
Customization:
Adjust HMA smoothing to make the centerline more or less responsive
Change how wide you want the bands to be
Turn different bands on or off as needed
The indicator combines advanced technical concepts (VWAP, HMA, volatility bands) in a visually clean way, using smoothing techniques to reduce noise and help identify clearer trading opportunities.
Hma Swing Points | viResearchHma Swing Points | viResearch
Conceptual Foundation and Innovation
The "Hma Swing Points" script introduces a simple yet effective method for identifying key swing points in the market using Hull Moving Averages (HMA). The Hull Moving Average is a faster and smoother alternative to traditional moving averages, making it ideal for detecting significant price swings. By applying HMA to both high and low prices, the script identifies swing highs and lows, providing traders with visual cues for potential trend reversals or continuations. This approach helps traders recognize turning points in the market with minimal lag, allowing for more precise entries and exits.
Technical Composition and Calculation
This script uses two Hull Moving Averages—one for the high prices and another for the low prices. These HMAs offer smoother trend detection while filtering out market noise. The script identifies the highest and lowest HMA values over a user-defined lookback period to determine the swing high and swing low points. Long signals are generated when the current HMA of the highs matches the highest value within the lookback period, while short signals are generated when the HMA of the lows matches the lowest value. These signals are plotted on the chart, and alerts can be set to notify the trader of possible entry or exit points.
Features and User Inputs
The script offers several customizable inputs to adjust its sensitivity and behavior according to the trader’s preferences. The lookback period defines the number of bars used to calculate the highest and lowest HMA values, allowing traders to control how responsive the script is to price changes. The length of the Hull Moving Average can also be modified, giving traders flexibility in smoothing the indicator. Additionally, optional bar color settings provide visual cues, with bullish and bearish trends highlighted. Alerts are included to notify traders when long or short swing points are detected, ensuring they are informed even when not actively monitoring the chart.
Practical Applications
The "Hma Swing Points" script is useful for traders who aim to identify critical market turning points and potential reversals. It is especially effective in trending markets where price swings present trading opportunities. Traders can use the script to detect reversals by spotting swing points that indicate a possible shift from bullish to bearish trends, or vice versa. The script also helps confirm ongoing trends by showing the strength of swings, allowing traders to make informed decisions about entering or exiting trades. Its ability to mark precise swing points enhances trade timing, helping traders optimize their entries and exits.
Advantages and Strategic Value
The script offers a streamlined approach to detecting swing points with the speed and smoothness of the Hull Moving Average. This makes it easier to filter out false signals and noise, improving the accuracy of trend identification. The customizable inputs allow traders to tailor the script for different assets and market conditions, making it versatile for various trading styles. By highlighting key swing points, the script provides traders with clear visual signals for potential reversals and trend confirmations, enhancing their ability to follow and act on market movements.
Summary and Usage Tips
Incorporating the "Hma Swing Points" script into a trading strategy helps traders identify market reversals and continuation points more effectively. Adjusting the lookback period and HMA length ensures the script adapts to different assets and market conditions. The alert system ensures traders don’t miss key swing points. As always, backtesting is important to evaluate the script’s performance under various market conditions, and past results may not guarantee future outcomes.
Reflected ema Difference (RED) This script, titled "Reflected EMA Difference (RED)," is based on the logic of evaluating the percentage of convergence and divergence between two moving averages, specifically the Hull Moving Averages (HMA), to make price-related decisions. The Hull Moving Average, created by Alan Hull, is used as the foundation of this strategy, offering a faster and more accurate way to analyze market trends. In this script, the concept is employed to measure and reflect price variations.
Script Functionality Overview:
Hull Moving Averages (HMA): The script utilizes two HMAs, one short-term and one long-term. The main idea is to compute the Delta Difference between these two moving averages, which represents how much they are converging or diverging from each other. This difference is key to identifying potential market trend changes.
Reflected HMA Value: Using the Delta Difference between the HMAs, the value of the short-term HMA is reflected, creating a visual reference point that helps traders see the relationship between price and HMAs on the chart.
Percentage Change Index: The second key parameter is the percentage change index. This determines when a trend is reversing, allowing buy or sell orders to be established based on significant changes in the relationship between the HMAs and the price.
Delta Multiplier: The script comes with a default Delta multiplier of 2 for calculating the difference between HMAs, allowing traders to adjust the sensitivity of the analysis based on the time frame being analyzed.
Trend Reversal Signals: When the price crosses the thresholds defined by the percentage change index, buy or sell signals are triggered, based on the detection of a potential trend reversal.
Visual Cues with Boxes: Boxes are drawn on the chart when the HullMA crosses the reflected HMA value, providing a visual aid to identify critical moments where risk should be evaluated.
Alerts for Receiving Signals:
This script allows you to set up buy and sell alerts via TradingView's alert system. These alerts are triggered when trend changes are detected based on the conditions coded in the script. Traders can receive instant notifications, allowing them to make decisions without needing to constantly monitor the chart.
Additional Considerations:
The percentage change parameter is adjustable and should be configured based on the time frame you are trading on. For longer time frames, it's advisable to use a larger percentage change to avoid false signals.
The use of Hull Moving Averages (HMA) provides a faster and more reactive approach to trend evaluation compared to other moving averages, making it a powerful tool for traders seeking quick reversal signals.
This approach combines the power of Hull Moving Averages with an alert system to improve the trader’s response to trend changes.
Spanish
Este script, titulado "Reflected EMA Difference (RED)", está fundamentado en la lógica de evaluar el porcentaje de acercamiento y distancia entre dos medias móviles, específicamente las medias móviles de Hull (HMA), para tomar decisiones sobre el valor del precio. El creador de la media móvil de Hull, Alan Hull, diseñó este indicador para ofrecer una forma más rápida y precisa de analizar tendencias de mercado, y en este script se utiliza su concepto como base para medir y reflejar las variaciones de precio.
Descripción del funcionamiento:
Medias Móviles de Hull (HMA): Se utilizan dos HMAs, una de corto plazo y otra de largo plazo. La idea principal es calcular la diferencia Delta entre estas dos medias móviles, que representa cuánto se están alejando o acercando entre sí. Esta diferencia es clave para identificar cambios potenciales en la tendencia del mercado.
Valor Reflejado de la HMA: Con la diferencia Delta calculada entre las HMAs, se refleja el valor de la HMA corta, creando un punto de referencia visual que ayuda a los traders a observar la relación entre el precio y las HMAs en el gráfico.
Índice de Cambio de Porcentaje: El segundo parámetro clave del script es el índice de cambio porcentual. Este define el momento en que una tendencia está revirtiendo, permitiendo establecer órdenes de compra o venta en función de un cambio significativo en la relación entre las HMAs y el precio.
Multiplicador Delta: El script tiene un multiplicador predeterminado de 2 para el cálculo de la diferencia Delta, lo que permite ajustar la sensibilidad del análisis según la temporalidad del gráfico.
Señales de Reversión de Tendencia: Cuando el precio cruza los límites definidos por el índice de cambio porcentual, se emiten señales para comprar o vender, basadas en la detección de una posible reversión de tendencia.
Visualización con Cajas: Se dibujan cajas en el gráfico cuando el indicador HullMA cruza el valor reflejado de la HMA, ayudando a identificar visualmente los momentos críticos en los que se debe evaluar el riesgo de las operaciones.
Alertas para Recibir Señales:
Este script permite configurar alertas de compra y venta desde el apartado de alertas de TradingView. Estas alertas se activan cuando se detectan cambios de tendencia en función de las condiciones establecidas en el código. El trader puede recibir notificaciones instantáneas, lo que facilita la toma de decisiones sin necesidad de estar constantemente observando el gráfico.
Consideraciones adicionales:
El porcentaje de cambio es un parámetro ajustable y debe configurarse según la temporalidad que se esté operando. En temporalidades más largas, es recomendable usar un porcentaje de cambio mayor para evitar señales falsas.
La utilización de las medias móviles de Hull (HMA) proporciona un enfoque más rápido y reactivo para evaluar tendencias en comparación con otras medias móviles, lo que lo convierte en una herramienta poderosa para traders que buscan señales rápidas de reversión.
Este enfoque combina la potencia de las medias móviles de Hull con un sistema de alertas que mejora la reactividad a cambios de tendencia.
Hull For Loop | viResearchHull For Loop | viResearch
Conceptual Foundation and Innovation
The "Hull For Loop" indicator brings together the smoothness and responsiveness of the Hull Moving Average (HMA) with a dynamic loop-based scoring system. The HMA is known for its ability to reduce lag while maintaining smooth trend representation, making it a popular choice for traders looking for a responsive and reliable moving average. By incorporating a for loop system that compares current and past HMA values over a user-defined range, the "Hull For Loop" script generates a score that allows traders to detect potential trend changes and assess the strength of ongoing trends. This combination of the HMA and a loop-based evaluation system provides traders with a powerful tool for understanding market momentum and making informed trading decisions.
Technical Composition and Calculation
The "Hull For Loop" script consists of two key elements: the Hull Moving Average (HMA) and the For Loop Scoring System. The HMA is calculated using a weighted moving average (WMA) of the price data, adjusted to reduce lag and provide a smoother trend line. The for loop compares the current HMA to past values over a customizable range, generating a score based on whether the current HMA is higher or lower than previous values.
For the Hull Moving Average, the calculation involves applying a WMA to the source price over the selected length. The result is then used in a secondary WMA calculation to further smooth the output and reduce lag. The For Loop Scoring System evaluates the HMA over a defined range (from and to) by adding or subtracting from the score depending on whether the current HMA is higher or lower than past values. This final score reflects the overall trend strength and direction.
Features and User Inputs
The "Hull For Loop" script offers several customizable inputs, allowing traders to tailor the indicator to their strategies. The Hull Length controls the period over which the HMA is calculated, affecting how quickly the indicator responds to price changes. The Loop Range (From and To) defines the range over which the for loop compares past HMA values, offering flexibility in assessing trend strength over different timeframes. Additionally, customizable thresholds allow traders to define when the score signals an uptrend or downtrend, providing control over the indicator's sensitivity to market conditions.
Practical Applications
The "Hull For Loop" indicator is designed for traders looking to capitalize on the smooth trend representation of the HMA while gaining insights into market momentum through a loop-based scoring system. This tool is particularly effective for identifying trend reversals, as the for loop scoring system provides early signals of potential trend reversals by comparing the current HMA to past values, giving traders an advantage in volatile markets. By analyzing the HMA across a range of past values, the indicator helps confirm whether trends are gaining or losing strength, improving trade entry and exit points. The customizable parameters allow traders to adjust the indicator to different market conditions, making it suitable for both short-term and long-term strategies.
Advantages and Strategic Value
The "Hull For Loop" script provides a significant advantage by combining the smoothness of the HMA with a dynamic scoring system. The HMA's ability to reduce lag while providing a clear trend signal makes it ideal for trend-following strategies, while the loop-based scoring system adds a layer of analysis that helps reduce false signals. This combination results in a reliable tool for identifying and confirming trends, allowing traders to adapt more effectively to changing market conditions.
Alerts and Visual Cues
The script includes alert conditions to notify traders of key trend changes. The "Hull For Loop Long" alert is triggered when the score crosses the upper threshold, signaling a potential upward trend. Conversely, the "Hull For Loop Short" alert signals a possible downward trend when the score crosses below the lower threshold. Visual cues, such as changes in the background color, highlight these trend shifts on the chart, helping traders quickly identify potential market reversals.
Summary and Usage Tips
The "Hull For Loop | viResearch" indicator offers traders a robust tool for trend analysis by combining the benefits of the Hull Moving Average with a dynamic loop-based scoring system. By incorporating this script into your trading strategy, you can improve your ability to detect and confirm trends with greater accuracy, reducing the impact of market noise. Whether you are focused on identifying early trend reversals or confirming ongoing trends, the "Hull For Loop" provides a reliable and customizable solution for traders of all levels.
Note: Backtests are based on past results and are not indicative of future performance.
HMA Smoothed RSI [Pinescriptlabs]This indicator uses a modified version of the RSI (Relative Strength Index) weighted by volume. This means it not only takes into account the price but also the amount of volume supporting those price movements, making the indicator more sensitive to real market fluctuations.
Hull Moving Average (HMA) Applied to RSI: To smooth the volume-weighted RSI, a Hull Moving Average (HMA) is applied. The HMA is known for its ability to reduce market "noise" and quickly react to trend changes. This process helps better identify when an asset is overbought or oversold.
Overbought and Oversold Regions: The indicator sets clear overbought and oversold levels, which are adjustable. By default, the overbought level is set at 20 and the oversold level at -20, but you can customize these values. Additionally, there are extreme overbought and oversold levels to help identify more extreme market conditions where a price reversal is more likely.
Buy and Sell Signals:
Buy Signal: This is generated when the modified RSI crosses above the oversold level. This indicates that the price has dropped enough and may be about to rise.
Sell Signal: This occurs when the RSI crosses below the overbought level. This suggests that the price has risen too much and could be about to fall.
Dynamic Visualization and Colors: The indicator is displayed with different colors based on its behavior:
When the RSI is within normal levels, the color is neutral.
If it is above the overbought level, the color turns red (sell alert).
If it is below the oversold level, the color turns green (buy alert).
Alerts: This indicator also allows you to set up alerts. You will receive automatic notifications when buy or sell signals are generated, helping you make decisions without constantly monitoring the chart.
Español:
Este indicador utiliza una versión modificada del RSI (Índice de Fuerza Relativa), ponderado por volumen. Esto significa que no solo tiene en cuenta el precio, sino también la cantidad de volumen que respalda esos movimientos de precios, haciendo que el indicador sea más sensible a las fluctuaciones reales del mercado.
Media Móvil Hull (HMA) aplicada al RSI: Para suavizar el RSI ponderado por volumen, se le aplica una Media Móvil Hull (HMA). La HMA es conocida por su capacidad para reducir el "ruido" del mercado y reaccionar rápidamente a los cambios de tendencia. Este proceso ayuda a identificar mejor cuándo un activo está sobrecomprado o sobrevendido.
Regiones de sobrecompra y sobreventa: El indicador establece niveles claros de sobrecompra y sobreventa que son ajustables. Por defecto, el nivel de sobrecompra está en 20 y el de sobreventa en -20, pero puedes personalizar estos valores. Además, hay niveles extremos de sobrecompra y sobreventa que te ayudan a identificar condiciones más extremas del mercado, donde una reversión de precio es más probable.
Señales de compra y venta:
Señal de compra: Se genera cuando el RSI modificado cruza hacia arriba el nivel de sobreventa. Esto indica que el precio ha bajado lo suficiente y puede estar a punto de subir.
Señal de venta: Se produce cuando el RSI cruza hacia abajo el nivel de sobrecompra. Esto indica que el precio ha subido demasiado y podría estar a punto de bajar.
Visualización y colores dinámicos: El indicador se muestra con diferentes colores según su comportamiento:
Cuando el RSI está dentro de los niveles normales, el color es neutro.
Si está por encima del nivel de sobrecompra, el color se vuelve rojo (señal de alerta de venta).
Si está por debajo del nivel de sobreventa, el color se vuelve verde (señal de alerta de compra).
Alertas: Este indicador también te permite configurar alertas. Así, recibirás notificaciones automáticas cuando se generen señales de compra o venta, ayudándote a tomar decisiones sin estar constantemente monitoreando el gráfico.
HMA Z-Score Probability Indicator by Erika BarkerThis indicator is a modified version of SteverSteves's original work, enhanced by Erika Barker. It visually represents asset price movements in terms of standard deviations from a Hull Moving Average (HMA), commonly known as a Z-Score.
Key Features:
Z-Score Calculation: Measures how many standard deviations the current price is from its HMA.
Hull Moving Average (HMA): This moving average provides a more responsive baseline for Z-Score calculations.
Flexible Display: Offers both area and candlestick visualization options for the Z-Score.
Probability Zones: Color-coded areas showing the statistical likelihood of prices based on their Z-Score.
Dynamic Price Level Labels: Displays actual price levels corresponding to Z-Score values.
Z-Table: An optional table showing the probability of occurrence for different Z-Score ranges.
Standard Deviation Lines: Horizontal lines at each standard deviation level for easy reference.
How It Works:
The indicator calculates the Z-Score by comparing the current price to its HMA and dividing by the standard deviation. This Z-Score is then plotted on a separate pane below the main chart.
Green areas/candles: Indicate prices above the HMA (positive Z-Score)
Red areas/candles: Indicate prices below the HMA (negative Z-Score)
Color-coded zones:
Green: Within 1 standard deviation (high probability)
Yellow: Between 1 and 2 standard deviations (medium probability)
Red: Beyond 2 standard deviations (low probability)
The HMA line (white) shows the trend of the Z-Score itself, offering insight into whether the asset is becoming more or less volatile over time.
Customization Options:
Adjust lookback periods for Z-Score and HMA calculations
Toggle between area and candlestick display
Show/hide probability fills, Z-Table, HMA line, and standard deviation bands
Customize text color and decimal rounding for price levels
Interpretation:
This indicator helps traders identify potential overbought or oversold conditions based on statistical probabilities. Extreme Z-Score values (beyond ±2 or ±3) often suggest a higher likelihood of mean reversion, while consistent Z-Scores in one direction may indicate a strong trend.
By combining the Z-Score with the HMA and probability zones, traders can gain a nuanced understanding of price movements relative to recent trends and their statistical significance.
Composite Z-Score with Linear Regression Bands [UAlgo]The Composite Z-Score with Linear Regression Bands is a technical indicator designed to provide traders with a comprehensive analysis of price momentum, volatility, and volume. By combining multiple moving averages with slope analysis, volume/volatility compression-expansion metrics, and Z-Score calculations, this indicator aims to highlight potential breakout and breakdown points with high accuracy. The inclusion of linear regression bands further enhances the analysis by providing dynamic support and resistance levels, which adapt to market conditions. This makes the indicator particularly useful in identifying overbought/oversold conditions, volume squeezes, and the overall direction of the trend.
🔶 Key Features
Multi-Length Slope Calculation: The indicator uses multiple Hull Moving Averages (HMA) across various lengths to calculate slope angles, which are then converted into Z-Scores. This helps in capturing both short-term and long-term price momentum.
Volume/Volatility Composite Analysis: By calculating a composite value derived from both volume and volatility, the indicator identifies periods of compression (squeezes) and expansion, which are crucial for detecting potential breakout opportunities.
Linear Regression Bands: The inclusion of dynamic linear regression bands provides traders with adaptive support and resistance levels. These bands are enhanced by the composite value, which adjusts the band width based on market conditions, offering a clearer view of possible price reversals.
Overbought/Oversold Detection: The indicator highlights overbought and oversold conditions by comparing Z-Scores against the upper and lower bounds of the regression bands, which can signal potential reversal points.
Customizable Inputs: Users can customize key parameters such as the lengths of the moving averages, the regression band period, and the number of deviations used for the bands, allowing for flexibility in adapting the indicator to different market environments.
🔶 Interpreting the Indicator
Z-Score Plots: The individual Z-Score plots represent the normalized slope of the Hull Moving Averages over different periods. Positive values indicate upward momentum, while negative values suggest downward momentum. The combined Z-Sum provides a broader view of the overall market momentum.
Composite Value: The composite value is a ratio of volume to volatility, which highlights periods of market compression and expansion. When the composite value rises, it suggests increasing market activity, often preceding a breakout.
Why are we calculating values for multiple lengths?
The Composite Z-Score with Linear Regression Bands indicator employs a multi-timeframe analysis by calculating Z-scores for various moving average lengths. This approach provides a more comprehensive view of market dynamics and helps to identify trends and potential reversals across different timeframes. By considering multiple lengths, we can:
Capture a broader range of market behaviors: Different moving average lengths capture different aspects of price movement. Shorter lengths are more sensitive to recent price changes, while longer lengths provide a smoother representation of the underlying trend.
Reduce the impact of noise: By combining Z-scores from multiple lengths, we can help to filter out some of the noise that can be present in shorter-term data and obtain a more robust signal.
Enhance the reliability of signals: When Z-scores from multiple lengths align, it can increase the confidence in the identified trend or potential reversal. This can help to reduce the likelihood of false signals.
In essence, calculating values for multiple lengths allows the indicator to provide a more nuanced and reliable assessment of market conditions, making it a valuable tool for traders and analysts.
Linear Regression Bands: The central line represents the linear regression of the Z-Sum, while the upper and lower bands represent the dynamic resistance and support levels, respectively. The deviation from the regression line indicates the strength of the current trend. When price moves beyond these bands, it may signal an overbought (above upper band) or oversold (below lower band) condition.
Volume/Volatility Squeeze: When the price moves between the regression bands and the volume/volatility-adjusted bands, the market is in a squeeze. Breakouts from this squeeze can lead to significant price moves, which are indicated by the filling of areas between the Z-Score plots and the bands.
Color Interpretation: The indicator uses color changes to make it easier to interpret the data. Teal colors generally indicate upward momentum or strong conditions, while red suggests downward momentum or weakening conditions. The intensity of the color reflects the strength of the signal.
Overbought/Oversold Signals: The indicator marks potential overbought and oversold conditions when Z-Scores cross above or below the upper and lower regression bands, respectively. These signals are crucial for identifying potential reversal points in the market.
🔶 Disclaimer
Use with Caution: This indicator is provided for educational and informational purposes only and should not be considered as financial advice. Users should exercise caution and perform their own analysis before making trading decisions based on the indicator's signals.
Not Financial Advice: The information provided by this indicator does not constitute financial advice, and the creator (UAlgo) shall not be held responsible for any trading losses incurred as a result of using this indicator.
Backtesting Recommended: Traders are encouraged to backtest the indicator thoroughly on historical data before using it in live trading to assess its performance and suitability for their trading strategies.
Risk Management: Trading involves inherent risks, and users should implement proper risk management strategies, including but not limited to stop-loss orders and position sizing, to mitigate potential losses.
No Guarantees: The accuracy and reliability of the indicator's signals cannot be guaranteed, as they are based on historical price data and past performance may not be indicative of future results.
Double CCI Confirmed Hull Moving Average Reversal StrategyOverview
The Double CCI Confirmed Hull Moving Average Strategy utilizes hull moving average (HMA) in conjunction with two commodity channel index (CCI) indicators: the slow and fast to increase the probability of entering when the short and mid-term uptrend confirmed. The main idea is to wait until the price breaks the HMA while both CCI are showing that the uptrend has likely been already started. Moreover, strategy uses exponential moving average (EMA) to trail the price when it reaches the specific level. The strategy opens only long trades.
Unique Features
Dynamic stop-loss system: Instead of fixed stop-loss level strategy utilizes average true range (ATR) multiplied by user given number subtracted from the position entry price as a dynamic stop loss level.
Configurable Trading Periods: Users can tailor the strategy to specific market windows, adapting to different market conditions.
Double trade setup confirmation: Strategy utilizes two different period CCI indicators to confirm the breakouts of HMA.
Trailing take profit level: After reaching the trailing profit activation level scrip activate the trailing of long trade using EMA. More information in methodology.
Methodology
The strategy opens long trade when the following price met the conditions:
Short-term period CCI indicator shall be above 0.
Long-term period CCI indicator shall be above 0.
Price shall cross the HMA and candle close above it with the same candle
When long trade is executed, strategy set the stop-loss level at the price ATR multiplied by user-given value below the entry price. This level is recalculated on every next candle close, adjusting to the current market volatility.
At the same time strategy set up the trailing stop validation level. When the price crosses the level equals entry price plus ATR multiplied by user-given value script starts to trail the price with EMA. If price closes below EMA long trade is closed. When the trailing starts, script prints the label “Trailing Activated”.
Strategy settings
In the inputs window user can setup the following strategy settings:
ATR Stop Loss (by default = 1.75)
ATR Trailing Profit Activation Level (by default = 2.25)
CCI Fast Length (by default = 25, used for calculation short term period CCI
CCI Slow Length (by default = 50, used for calculation long term period CCI)
Hull MA Length (by default = 34, period of HMA, which shall be broken to open trade)
Trailing EMA Length (by default = 20)
User can choose the optimal parameters during backtesting on certain price chart.
Justification of Methodology
Before understanding why this particular combination of indicator has been chosen let's briefly explain what is CCI and HMA.
The Commodity Channel Index (CCI) is a momentum-based technical indicator used in trading to measure a security's price relative to its average price over a given period. Developed by Donald Lambert in 1980, the CCI is primarily used to identify cyclical trends in a security, helping traders to spot potential buying or selling opportunities.
The CCI formula is:
CCI = (Typical Price − SMA) / (0.015 × Mean Deviation)
Typical Price (TP): This is calculated as the average of the high, low, and closing prices for the period.
Simple Moving Average (SMA): This is the average of the Typical Prices over a specific number of periods.
Mean Deviation: This is the average of the absolute differences between the Typical Price and the SMA.
The result is a value that typically fluctuates between +100 and -100, though it is not bounded and can go higher or lower depending on the price movement.
The Hull Moving Average (HMA) is a type of moving average that was developed by Alan Hull to improve upon the traditional moving averages by reducing lag while maintaining smoothness. The goal of the HMA is to create an indicator that is both quick to respond to price changes and less prone to whipsaws (false signals).
How the Hull Moving Average is Calculated?
The Hull Moving Average is calculated using the following steps:
Weighted Moving Average (WMA): The HMA starts by calculating the Weighted Moving Average (WMA) of the price data over a period square root of n (sqrt(n))
Speed Adjustment: A WMA is then calculated for half of the period n/2, and this is multiplied by 2 to give more weight to recent prices.
Lag Reduction: The WMA of the full period n is subtracted from the doubled n/2 WMA.
Final Smoothing: To smooth the result and reduce noise, a WMA is calculated for the square root of the period n.
The formula can be represented as:
HMA(n) = WMA(WMA(n/2) × 2 − WMA(n), sqrt(n))
The Weighted Moving Average (WMA) is a type of moving average that gives more weight to recent data points, making it more responsive to recent price changes than a Simple Moving Average (SMA). In a WMA, each data point within the selected period is multiplied by a weight, with the most recent data receiving the highest weight. The sum of these weighted values is then divided by the sum of the weights to produce the WMA.
This strategy leverages HMA of user given period as a critical level which shall be broken to say that probability of trend change to the upside increased. HMA reacts faster than EMA or SMA to the price change, that’s why it increases chances to enter new trade earlier. Long-term period CCI helps to have an approximation of mid-term trend. If it’s above 0 the probability of uptrend increases. Short-period CCI allows to have an approximation of short-term trend reversal from down to uptrend. This approach increases chances to have a long trade setup in the direction of mid-term trend when the short-term trend starts to reverse.
ATR is used to adjust the strategy risk management to the current market volatility. If volatility is low, we don’t need the large stop loss to understand the there is a high probability that we made a mistake opening the trade. User can setup the settings ATR Stop Loss and ATR Trailing Profit Activation Level to realize his own risk to reward preferences, but the unique feature of a strategy is that after reaching trailing profit activation level strategy is trying to follow the trend until it is likely to be finished instead of using fixed risk management settings. It allows sometimes to be involved in the large movements. It’s also important to make a note, that script uses HMA to enter the trade, but for trailing it leverages EMA. It’s used because EMA has no such fast reaction to price move which increases probability not to be stopped out from any significant uptrend move.
Backtest Results
Operating window: Date range of backtests is 2022.07.01 - 2024.08.01. It is chosen to let the strategy to close all opened positions.
Commission and Slippage: Includes a standard Binance commission of 0.1% and accounts for possible slippage over 5 ticks.
Initial capital: 10000 USDT
Percent of capital used in every trade: 100%
Maximum Single Position Loss: -4.67%
Maximum Single Profit: +19.66%
Net Profit: +14897.94 USDT (+148.98%)
Total Trades: 104 (36.54% win rate)
Profit Factor: 2.312
Maximum Accumulated Loss: 1302.66 USDT (-9.58%)
Average Profit per Trade: 143.25 USDT (+0.96%)
Average Trade Duration: 34 hours
These results are obtained with realistic parameters representing trading conditions observed at major exchanges such as Binance and with realistic trading portfolio usage parameters.
How to Use
Add the script to favorites for easy access.
Apply to the desired timeframe and chart (optimal performance observed on 2h BTC/USDT).
Configure settings using the dropdown choice list in the built-in menu.
Set up alerts to automate strategy positions through web hook with the text: {{strategy.order.alert_message}}
Disclaimer:
Educational and informational tool reflecting Skyrex commitment to informed trading. Past performance does not guarantee future results. Test strategies in a simulated environment before live implementation
Normalized Hull Moving Average Oscillator w/ ConfigurationsThis indicator uniquely uses normalization techniques applied to the Hull Moving Average (HMA) and allows the user to choose between a number of different types of normalization, each with their own advantages. This indicator is one in a series of experiments I've been working on in looking at different methods of transforming data. In particular, this is a more usable example of the power of data transformation, as it takes the Hull Moving Average of Alan Hull and turns it into a powerful oscillating indicator.
The indicator offers multiple types of normalization, each with its own set of benefits and drawbacks. My personal favorites are the Mean Normalization , which turns the data series into one centered around 0, and the Quantile Transformation , which converts the data into a data set that is normally distributed.
I've also included the option of showing the mean, median, and mode of the data over the period specified by the length of normalization. Using this will allow you to gather additional insights into how these transformations affect the distribution of the data series.
Types of Normalization:
1. Z-Score
Overview: Standardizes the data by subtracting the mean and dividing by the standard deviation.
Benefits: Centers the data around 0 with a standard deviation of 1, reducing the impact of outliers.
Disadvantages: Works best on data that is normally distributed
Notes: Best used with a mid-longer length of transformation.
2. Min-Max
Overview: Scales the data to fit within a specified range, typically 0 to 1.
Benefits: Simple and fast to compute, preserves the relationships among data points.
Disadvantages: Sensitive to outliers, which can skew the normalization.
Notes: Best used with mid-longer length of transformation.
3. Mean Normalization
Overview: Subtracts the mean and divides by the range (max - min).
Benefits: Centers data around 0, making it easier to compare different datasets.
Disadvantages: Can be affected by outliers, which influence the range.
Notes: Best used with a mid-longer length of transformation.
4. Max Abs Scaler
Overview: Scales each feature by its maximum absolute value.
Benefits: Retains sparsity and is robust to large outliers.
Disadvantages: Only shifts data to the range , which might not always be desirable.
Notes: Best used with a mid-longer length of transformation.
5. Robust Scaler
Overview: Uses the median and the interquartile range for scaling.
Benefits: Robust to outliers, does not shift data as much as other methods.
Disadvantages: May not perform well with small datasets.
Notes: Best used with a longer length of transformation.
6. Feature Scaling to Unit Norm
Overview: Scales data such that the norm (magnitude) of each feature is 1.
Benefits: Useful for models that rely on the magnitude of feature vectors.
Disadvantages: Sensitive to outliers, which can disproportionately affect the norm. Not normally used in this context, though it provides some interesting transformations.
Notes: Best used with a shorter length of transformation.
7. Logistic Function
Overview: Applies the logistic function to squash data into the range .
Benefits: Smoothly compresses extreme values, handling skewed distributions well.
Disadvantages: May not preserve the relative distances between data points as effectively.
Notes: Best used with a shorter length of transformation. This feature is actually two layered, we first put it through the mean normalization to ensure that it's generally centered around 0.
8. Quantile Transformation
Overview: Maps data to a uniform or normal distribution using quantiles.
Benefits: Makes data follow a specified distribution, useful for non-linear scaling.
Disadvantages: Can distort relationships between features, computationally expensive.
Notes: Best used with a very long length of transformation.
Conclusion
This indicator is a powerful example into how normalization can alter and improve the usability of a data series. Each method offers unique insights and benefits, making this indicator a useful tool for any trader. Try it out, and don't hesitate to reach out if you notice any glaring flaws in the script, room for improvement, or if you just have questions.
No Lag SupertrendNo Lag Supertrend indicator improves upon the original supertrend by incorporating calculation methods that enhance responsiveness and accuracy. Traditional supertrend indicators often suffer from lag, which can delay signals and affect trading decisions. No Lag Supertrend addresses this issue through the use of KAMA (Kaufman’s Adaptive Moving Average) and Hull ATR (Average True Range) calculations.
Goals of No Lag Supertrend:
- Lag reduction: one of the main issues with traditional supertrend indicators is their lag, which can result in delayed entry and exit signals. By integrating KAMA and Hull ATR, the no lag supertrend minimizes this delay, providing more timely signals.
- Market Noise Filtering: The combined use of KAMA and Hull ATR effectively filters out market noise, ensuring that signals are based on significant price movements rather than minor fluctuations.
- Consistency Across Different Market Conditions: The adaptive nature of KAMA and the smooth responsiveness of Hull ATR ensure that the No Lag Supertrend performs consistently across various market conditions, from trending to volatile markets.
Credits: This code is based on the TradingView supertrend but improved the ATR calculations.
No-Lag MA Crossover ScalperThe No Lag Crossover Scalper aims to capitalize on short-term trends using a combination of Hull Moving Average (HMA) for trend detection and multiple indicators for generating buy and sell signals. Here’s an overview of its components and approach:
1. Trend Detection with Hull Moving Averages (HMA) :
- Dual Hull MA Setup : Uses two Hull Moving Averages (HMA) to detect crossovers and crossunders, which are signals of short-term trend changes.
- No Lag Nature : HMAs are chosen for their ability to reduce lag compared to traditional moving averages, providing quicker responses to price movements.
2. Indicators for Signal Generation :
- Relative Strength Index (RSI) : Detects overbought and oversold conditions, generating signals when price movements diverge from RSI readings.
- Moving Average Convergence Divergence (MACD) : Provides signals based on the convergence and divergence of two moving averages, indicating potential trend reversals.
- Stochastic Oscillator (Stoch) : Identifies momentum shifts by comparing the current closing price to its range over a specific period.
- On-Balance Volume (OBV) : Measures buying and selling pressure based on volume flow, signaling potential changes in price direction.
- RSI Divergence : Looks for discrepancies between price action and RSI values, suggesting weakening trends and possible reversals.
3. Signal Generation Logic :
- Buy Signals : Generated when both HMAs cross over, supported by bullish indications from RSI, MACD, Stoch, OBV, or RSI divergence. At least 2 indicators must be true to generate a signal.
- Sell Signals : Triggered when HMAs cross under, complemented by bearish signals from the mentioned indicators.
4. Implementation and Optimization :
- Parameter Optimization : Fine-tuning of indicator periods and sensitivity settings to balance signal accuracy and responsiveness.
- Confirmation Mechanisms : Use of multiple indicators to confirm signals, reducing false positives and enhancing reliability.
Overall, the No Lag Crossover Scalper combines the speed of Hull Moving Averages with the reliability of multiple indicators to identify short-term trends effectively. By focusing on no lag indicators and confirming signals with diverse technical tools, it aims to capitalize on rapid market movements while managing risk through disciplined execution.
Credits: used TradingView ta library for a lot of the built-in indicators.
Disclaimer: This is still experimental beta version so use at your own risk.
HMA Crossover 1H with RSI, Stochastic RSI, and Trailing StopThe strategy script provided is a trading algorithm designed to help traders make informed buy and sell decisions based on certain technical indicators. Here’s a breakdown of what each part of the script does and how the strategy works:
Key Components:
Hull Moving Averages (HMA):
HMA 5: This is a Hull Moving Average calculated over 5 periods. HMAs are used to smooth out price data and identify trends more quickly than traditional moving averages.
HMA 20: This is another HMA but calculated over 20 periods, providing a broader view of the trend.
Relative Strength Index (RSI):
RSI 14: This is a momentum oscillator that measures the speed and change of price movements over a 14-period timeframe. It helps identify overbought or oversold conditions in the market.
Stochastic RSI:
%K: This is the main line of the Stochastic RSI, which combines the RSI and the Stochastic Oscillator to provide a more sensitive measure of overbought and oversold conditions. It is smoothed with a 3-period simple moving average.
Trading Signals:
Buy Signal:
Generated when the 5-period HMA crosses above the 20-period HMA, indicating a potential upward trend.
Additionally, the RSI must be below 45, suggesting that the market is not overbought.
The Stochastic RSI %K must also be below 39, confirming the oversold condition.
Sell Signal:
Generated when the 5-period HMA crosses below the 20-period HMA, indicating a potential downward trend.
The RSI must be above 60, suggesting that the market is not oversold.
The Stochastic RSI %K must also be above 63, confirming the overbought condition.
Trailing Stop Loss:
This feature helps protect profits by automatically selling the position if the price moves against the trade by 5%.
For sell positions, an additional trailing stop of 100 points is included.
Nasan Moving AverageNasan Moving Average belong to the group of moving average which provides a high degree of smoothness with very low lag.
The calculation process involves several steps to analyze the typical price of a financial asset over specific periods. It starts by computing a simple moving average and standard deviation of the typical price. Then, it standardizes (differencing TP - Average Typical price over previous n periods) the price and applies an inverse hyperbolic sine transformation to the standardized value. The transformed values are summed cumulatively, and various weighted moving averages are calculated to adjust and smooth the data. The final output is a smoothed signal with reduced lag.
Input Parameters:
len: Differencing length (default 21, Use a minimum of 5 and for lower time frames less than 15 min use values between 300 -3000)
len1: Correction Factor Length 1 (default 21, this determines the length of the MA you want , eg. 10 MA, 50 MA, 100 MA, )
len2: Correction Factor Length 2 (default 9, this works best if it is ~ </=1/2 of len1 )
len3: Smoothing Length (default 5, I would not change this and only use if I want to introduce lag where you want to use it for cross over strategies).
Differencing and Standardization:
The code calculates the standardized price a by differencing the typical price and normalizing it using the mean and standard deviation. This step standardizes the price changes.
Transformation:
The transformation using logarithms and square roots (b) aim to stabilize the variance and make the distribution more normal-like, improving the robustness of the cumulative sum c.
Cumulative Sum:
The cumulative sum c of the transformed series helps in integrating the series over time, capturing the overall trend and movement.
Correction Factors:
Correction factors c1 and c4 adjust the cumulative sum based on weighted averages, to correct any biases or to align it with the typical price.
Smoothing:
The final result c6 is smoothed using a weighted moving average, reducing noise and making it easier to interpret trends.
Fibonacci Moving Averages [UkutaLabs]█ OVERVIEW
The Fibonacci Moving Averages are a toolkit which allows the user to configure different types of Moving Averages based on key Fibonacci numbers.
Moving Averages are used to visualise short-term and long-term support and resistance which can be used as a signal where price might continue or retrace. Moving Averages serve as a simple yet powerful tool that can help traders in their decision-making and help foster a sense of where the price might be moving next.
The aim of this script is to simplify the trading experience of users by automatically displaying a series of useful Moving Averages, allowing the user to easily configure multiple at once depending on their trading style.
█ USAGE
This script will automatically plot 5 Moving Averages, each with a period of a key Fibonacci Level (5, 8, 13, 21 and 34).
Both the Source and Type of the Moving Averages can be configured by the user (see all options below under SETTINGS), making this a versatile trading tool that can provide value in a wide variety of trading styles.
█ SETTINGS
Configuration
• MA Source: Determines the source of the Moving Averages (open, high, low, close, hl2, hlc3, ohlc4, hlcc4)
• MA Source: Determines the type of the Moving Averages (SMA, EMA, VWMA, WMA, HMA, RMA)
Colors
• 5: Determines the color of the 5 period Moving Average
• 8: Determines the color of the 8 period Moving Average
• 13: Determines the color of the 13 period Moving Average
• 21: Determines the color of the 21 period Moving Average
• 34: Determines the color of the 34 period Moving Average
Papercuts Recency CandlesPapercuts Recency Candles
V0.8 by Joel Eckert @PapercutsTrading
***This is currently an experimental visual exploratory concept.***
*** Experimental tools should only be explored by fellow coders and experienced traders.***
DESCRIPTION:
As coders, how can we seamlessly transition between actual and smoothed price data sets as data ages?
This is a visual experiment to see if and how data can be smoothly transitioned from one value to another over a set number of candles. If we visualize a chart in 3 zones, a head, a body, and a tail we can start to understand how this could work. The head zone would represent the first data set of actual asset prices. The body zone would represent the transition period from the first to the to the second data set. Last, the tail zone would represent the second data set made of a Hull Moving Average of the asset.
CONCEPT:
It is conceived that data and position precision constantly shift as they decay or age, therefore making older price levels act more like price regions or zones vs exact price points. This is what I am calling Recency.
This indicator utilizes the concept of "Recency" to explore the possibility of a new style of candle. It aims to maintain accurately on recent prices action but loosen up accuracy on older price action. The very nature of this requires ALTERING HISTORICAL DATA within the body zone or transition candles to achieve the effect. It is similar to trying to merge a line chart type with a candle chart type.
This experiment of using recency for candles was to create candles that stay more accurate near current price but fade away into a simple line as they age out, resulting in a simplified view of the big picture which consists of older price action.
This experimental design theoretically will help you stay focused only on what is currently unfolding and to minimize distractions from older price nuances.
USAGE:
WHO:
This is not recommended for new traders or novices that are unfamiliar with standard tools. Standardized tools should always be used to get grounded and build a foundation.
Active traders who are familiar with trading comfortably should experiment with this to see if they find it interesting or usable.
Pine coders may find this concept interesting enough, and may adapt the idea to other elements of their own scripts if they find it interesting… I just ask they give credit where credit is due.
HOW:
The best way to visualize how this works is to do the following:
Load it on a chart.
Turn off Standard candles in Chart Setting of the current window. I actually just turn off the bodies and borders, and dim the old wicks as I like the way the old wicks look when left alone with these new candles.
Enable chart replay at a faster speed, like 3x, and play back the chart to watch the behavior of the candles.
You’ll be able to see how the head of the candle type preserves OHLC, and indicates direction but as the candle starts to age it progressively flowers into the HMA
While it plays back try adjusting settings to see how they affect behavior.
You can see the data average in real-time which often reveals how unstable actual price noise really is.
The head candle diagonals indicate the candle body direction.
SETTINGS:
Coloring: You can choose your own bullish or bearish colors to match your scheme.
Price Line: The price line is colored according to the trend and
Head Length: These candles are true to the source high and low. They remain slightly brighter than transition candles. We have a max of 50 to keep things responsive.
Time Decay Length: This is the amount of candles it takes to transition to the tail. Max is 300 to keep things responsive.
Decay Continuity: This forces transition candles to complete the HMA curve instead of creating gaps when conforming to it. The best way to visualize this feature is to run a 3x replay of an asset, and toggle the result on and off. On is preferred.
Tail HMA Length: This is the smoothing amount for the resulting HMA stepline that calculates every close, but has a delayed draw until after the transition candles. You can optionally turn off the delayed visibility to help with comprehension.
Tail HMA Weight: This is simply an option to make the tail thicker or thinner. This also adjusts the border on the head candles to help them stand out.
Show Side Bias Dots: Default true: Draws a dot when bias to one side changes to help keep you on the right side of trade. Side bias is simply the alignment of 3 moving averages in one direction.
IMPORTANT NOTES:
You'll have to turn off or dim the standard candles in your view "Chart Settings" to see this properly.
Be aware that since the candles are based on boxes and utilize the “recency concept”, which means their data decays and changes as it ages. This results in a cleaner chart overall, but exact highs and lows will be averaged out as the data decays, forming a Hull Moving Average stepline of your defined length once decay has finished.
SUMMARY OF HOW IT WORKS:
First it takes candle information and creates unique boxes that represent each candle based on the high and low. It utilizes boxes because standard candles once written, cannot be later altered or removed… which is a key element for this effect to work.
Next it creates a second box and line from open to close for the body of the Head candles. This indicates direction at a glance.
As candles age beyond the defined distance of the “Head” they enter the "Body" aka "Time Decay" zone. Here the accuracy of the high and low will be averaged down using an incremental factor of the HMA, defined by "Time Decay Length" amount of candles.
The resulting tail is an HMA of Tail HMA Length. This tail is always calculate at close, but is not drawn instantly. The draw is delayed so that there is not overlapping data, and this makes the effect look more elegant.
There are also two EMAs within the script that do nothing but help candle coloring and help provide a trade side bias. When both EMA's and the HMA align, a side bias is defined. Only when the side bias changes will a new dot is formed.
Head candles have been simplified from previous versions to be easier to read at a a glance.
F.B_Double Hull Moving Average Trend TrackerThe F.B_Double Hull Moving Average Trend Tracker indicator is designed to identify market trends and is based on two Hull Moving Averages.
The "Hull Moving Average" (HMA) is a fast and smooth moving average that exhibits a rather unique behavior. The HMA attempts to completely remove lag while simultaneously presenting smoother results.
The first derivative is calculated for each HMA 1 and HMA 2.
If HMA 1 derivative > 0 and HMA 2 derivative > 0, then color the HMA lines and bar color green.
If HMA 1 derivative < 0 and HMA 2 derivative < 0, then color the HMA lines and bar color red.
If the slope of the derivative is different between HMA 1 and HMA 2, then color the HMA lines and bar color gray.
Meaning of colors:
Green ⇒ Uptrend
Gray ⇒ Price consolidation, trend weakness, or correction
Red ⇒ Downtrend
Best used in conjunction with additional indicators.
Advanced Trend Strategy [BITsPIP]The BITsPIP team is super excited to share our latest trading gem with you all. We're all about diving deep and ensuring our strategies can stand the test of time. So, we invite you to join us in exploring the awesome potential of this new strategy and really put it through its pace with some deep backtesting. This isn't just another strategy; it boasts a profit factor hovering around 1.5 across over 1000 trades, which is quite an achievement. Consider integrating it with your trading bots to further enhance your trading efficiency and profit generation. Curious? Ask for trial access or drop by our website for more details.
I. Deep Backtesting
We're all in on transparency and solid results, which is why we didn't stop at 100... or even 500 trades. We went over 1000, making sure this strategy is as robust as they come. No flimsy forecasts or sneaky repainting here. Just good, solid strategy that's ready for the real deal. Curious about the details? Check out our detailed backtesting screenshot for the BINANCE:BTCUSDT in a 5-minute timeframe. It's all about giving you the clear picture.
#No Overfitting
#No Repainting
Backtesting Screenshot
II. Algorithmic Trading
Thinking of trading as a manual game? Think again! Manual trading is a bit like rolling the dice - fun, but kind of risky if you're aiming for consistent wins. Instead, why not lean into the future with algorithmic trading? It's all about trusting the market's rhythm over the long term. By integrating your strategy with a trading bot, you can enjoy peace of mind, rest easy, and keep those emotional trades at bay.
III) Applications
Dive into the Advanced Trend Strategy, your versatile tool for navigating the market's waters. This strategy shines in under an hour timeframes, offering adaptability across stocks, commodities, forex, and cryptocurrencies. Initially fine-tuned for low-volatility cryptos like BINANCE:BTCUSDT , its default settings are a solid starting point.
But here's where your expertise comes into play. Each market beats to its own drum, necessitating nuanced adjustments to stop loss and take profit settings. This customization is key to maximizing the strategy's effectiveness in your chosen arena.
IV) Strategy's Logic
The Advanced Trend Strategy is a powerhouse, blending the precision of Hull Suite, RSI, and our unique trend detector technique. At its core, it’s designed for savvy risk management, aiming to lock in substantial profits while steering clear of minor market ripples. It utilizes stop-loss and take-profit thresholds to form a profit channel, providing a safety net for each trade. This is a trend-following strategy at heart, where these profit channels play a critical role in maximizing returns by securing positions within these "warranty channels."
1. Trend-Following
The market's complexity, influenced by countless factors, makes small movements seem almost chaotic. Yet, the principle of #Trend-Following shines in less volatile markets in long term. The strategy excels by pinpointing the ideal moments to enter the market, coupled with refined risk management to secure profits. It’s tailored for you, the individual trader, enabling you to ride the waves of market trends upwards or downwards.
2. Risk Management
A key facet of the strategy is its emphasis on pragmatic risk management. Traders are empowered to establish practical stop-loss and take-profit levels, tailoring these crucial parameters to the specific market they are engaging in. This customization is instrumental in optimizing long-term profitability, ensuring that the strategy adapts fluidly to the unique characteristics and volatility patterns of different trading environments.
V) Strategy's Input Settings and Default Values
1. Alerts
The strategy comes equipped with a flexible alert system designed to keep you informed and ready to act. Within the settings, you’ll find options to configure order/exit and comment/alert messages to your preference. This feature is particularly useful for staying on top of the strategy’s activities without constant manual oversight.
2. Hull Suite
i. Hull Suite Length: Designed for capturing long-term trends, the Hull Suite Length is configured at 1000. Functioning comparably to moving averages, the Hull Suite features upper and lower bands. Currently, it is set to 1000.
ii. Length Multiplier: It's advisable to maintain a minimal value for the Length Multiplier, prioritizing the optimization of the Hull Suite Length. Presently, it is set to 1.
3. RSI Indicator
i. The RSI is a widely recognized tool in trading. Adapt the oversold and overbought thresholds to better match the specifics of your market for optimal results.
4. StopLoss and TakeProfit
i. StopLoss and TakeProfit Settings: Two distinct approaches are available. Semi-Automatic StopLoss/TakeProfit Setting and Manual StopLoss/TakeProfit Setting. The Semi-Automatic mode streamlines the process by allowing you to input values for a 5-minute timeframe, subsequently auto-adjusting these values across various timeframes, both lower and higher. Conversely, the Manual mode offers full control, enabling you to meticulously define TakeProfit values for each individual timeframe.
ii. TakeProfit Threshold # and TakeProfit Value #: Imagine this mechanism as an ascending staircase. Each step represents a range, with the lower boundary (TakeProfit Value) designed to close the trade upon being reached, and the upper boundary (TakeProfit Threshold) upon being hit, propelling the trade to the next level, and forming a new range. This stair-stepping approach enhances risk management and increases profitability. The pre-set configurations are tailored for $BINANCE:BTCUSDT. It's advisable to devote time to tailoring these settings to your specific market, aiming to achieve optimal results based on backtesting.
iii. StopLoss Value: In line with its name, this value marks the limit of loss you're prepared to accept should the market trend go against your expectations. It's crucial to note that once your asset reaches the first TakeProfit range, the initial StopLoss value becomes obsolete, supplanted by the first TakeProfit Value. The default StopLoss value is pegged at 1.6(%), a figure worth considering in your trading strategy.
VI) Entry Conditions
The primary signal for entry is generated by our custom trend detection mechanism and hull suite values (ascending/descending). This is supported by additional indicators acting as confirmation.
VII) Exit Conditions
The strategy stipulates exit conditions primarily governed by stop loss and take profit parameters. On infrequent occasions, if the trend lacks confirmation post-entry, the strategy mandates an exit upon the issuance of a reverse signal (whether confirmed or unconfirmed) by the strategy itself.
BITsPIP
Trend, Momentum, Volume Delta Ratings Emoji RatingsThis indicator provides a visual summary of three key market conditions - Trend, Momentum, and Volume Delta - to help traders quickly assess the current state of the market. The goal is to offer a concise, at-a-glance view of these important technical factors.
Trend (HMA): The indicator uses a Hull Moving Average (HMA) to assess the overall trend direction. If the current price is above the HMA, the trend is considered "Good" or bullish (represented by a 😀 emoji). If the price is below the HMA, the trend is "Bad" or bearish (🤮). If the price is equal to the HMA, the trend is considered "Neutral" (😐).
Momentum (ROC): The Rate of Change (ROC) is used to measure the momentum of the market. A positive ROC indicates "Good" or bullish momentum (😀), a negative ROC indicates "Bad" or bearish momentum (🤮), and a zero ROC is considered "Neutral" (😐).
Volume Delta: The indicator calculates the difference between the current trading volume and a simple moving average of the volume (Volume Delta). If the Volume Delta is above a user-defined threshold, it is considered "Good" or bullish (😀). If the Volume Delta is below the negative of the threshold, it is "Bad" or bearish (🤮). Values within the threshold are considered "Neutral" (😐).
The indicator displays these three ratings in a compact table format in the top-right corner of the chart. The table uses color-coding to quickly convey the overall market conditions - green for "Good", red for "Bad", and gray for "Neutral".
This indicator can be useful for traders who want a concise, at-a-glance view of the current market trend, momentum, and volume activity. By combining these three technical factors, traders can get a more well-rounded understanding of the market conditions and potentially identify opportunities or areas of concern more easily.
The user can customize the indicator by adjusting the lengths of the HMA, ROC, and Volume moving average, as well as the Volume Delta threshold. The colors used in the table can also be customized to suit the trader's preferences.
SVMKR_UT_Bot_HMA_UCS_LRSThis Pine Script code is a TradingView study script titled "SVMKR_UT_Bot_HMA_UCS_LRS". It combines two separate trading indicators: the UT Bot (Ultimate Trailing Stop Bot) and the UCS_LRS (Linear Regression Slope) indicator.
UT Bot (Ultimate Trailing Stop Bot):
The UT Bot is designed to provide buy and sell signals based on a trailing stop strategy.
It calculates the trailing stop level using the Average True Range (ATR) and Heikin Ashi candle signals if enabled.
Buy signals are generated when the price crosses above the trailing stop, while sell signals occur when the price crosses below the trailing stop.
Additionally, buy and sell signals are visually represented on the chart with corresponding labels and shapes.
The script also includes options to customize the sensitivity of the trailing stop and to color the bars based on buy or sell signals.
Hull Moving Average (HMA):
This section calculates and plots the Hull Moving Average, a type of moving average that reduces lag and improves smoothing compared to traditional moving averages.
It uses the weighted moving average (WMA) to compute the HMA, which helps to identify trend direction and potential reversal points.
UCS_LRS (Linear Regression Slope):
The UCS_LRS indicator calculates the linear regression slope of the closing prices over a specified period.
It then applies exponential smoothing to the slope values and calculates an average slope.
Buy signals are generated when the current slope is greater than the average slope and positive, indicating an uptrend.
Conversely, sell signals are generated when the current slope is less than the average slope and negative, suggesting a downtrend.
The linear regression slope and its average are plotted on the chart, allowing traders to visually identify trend strength and potential reversal points.
Overall, this combined script provides traders with a comprehensive set of tools for trend following and momentum trading strategies, integrating trailing stop analysis, moving average smoothing, and linear regression slope analysis into a single script for technical analysis on TradingView charts.
Hull AMA SignalsThis script is a comprehensive trading indicator named "Hull AMA Signals", which combines AMA and HSO by LuxAlgo and ther video based strategy techniques to provide buy (long) and sell (short) signals. It overlays directly on the price chart, offering a dynamic and visually intuitive trading aid. The core components of this indicator are Adaptive Moving Averages (AMA), Hull Moving Average (HMA), and a unique Hull squeeze oscillator (HSO), each configured with customizable parameters for flexibility and adaptability to various market conditions.
Features and Components
Adaptive Moving Averages (AMA): This indicator employs two sets of AMAs, each with distinct lengths, multipliers, lags, and overshoot parameters. The AMAs are designed to adapt their sensitivity based on the market's volatility, making them more responsive during significant price movements and less prone to false signals during periods of consolidation.
Hull Moving Average (HMA): The HMA is calculated using a sophisticated algorithm that aims to reduce the lag commonly associated with traditional moving averages. It provides a smoother and more responsive moving average line, which helps in identifying the prevailing market trend more accurately.
Hull Squeeze Oscillator (HSO): A novel component of this indicator, the HSO, is designed to identify potential market breakouts. It does so by comparing the Hull Moving Average's direction and momentum against a dynamically calculated mean, generating bullish or bearish signals based on the crossover and divergence from this mean.
Buy (Long) and Sell (Short) Signals: The script intelligently combines signals from the AMA crossovers and the Hull squeeze oscillator to pinpoint potential buy and sell opportunities. Bullish signals are generated when there's a positive crossover in the AMAs accompanied by a bullish dot from the HSO, whereas bearish signals are indicated by a negative crossover in the AMAs along with a bearish dot from the HSO.
Customization and Style Options: Users have the ability to adjust various parameters such as the length of the moving averages, multipliers, and source data, enabling customization for different trading strategies and asset classes. Additionally, color-coded visual elements like gradients and shapes enhance the readability and instant recognition of trading signals.
Use Cases
Trend Identification: By analyzing the direction and position of the AMAs and HMA, traders can easily discern the prevailing market trend, helping them to align their trades with the market momentum.
Signal Confirmation: The combination of AMA crossovers and HSO signals provides a robust framework for confirming trade entries and exits, potentially increasing the reliability of the trading signals.
Volatility Adaptation: The adaptive nature of the AMAs and the dynamic calculation of the HSO mean allow this indicator to adjust to changing market volatility, making it suitable for a wide range of market environments.
This indicator is suitable for traders looking for a comprehensive and dynamic technical analysis tool that combines trend analysis with signal generation, offering both visual appeal and practical trading utility.
