Daily Session DividerThis script draws vertical lines showing the new daily sessions. These will only be displayed when it's on an intraday timeframe (lower than daily timeframe).
Settings:
Line Color: Choose the color you want and change the opacity
Line Width: If you want a thicc line. Defaults to 1 (recommended setting)
Line Style: Choose between solid (default), dashed, or dotted
Chart
PDF-MA Supertrend [BackQuant]PDF-MA Supertrend
The PDF-MA Supertrend combines the innovative Probability Density Function (PDF) smoothing with the widely popular Supertrend methodology, creating a robust tool for identifying trends and generating actionable trading signals. This indicator is designed to provide precise entries and exits by dynamically adapting to market volatility while visualizing long and short opportunities directly on the chart.
Core Feature: PDF Smoothing
At the foundation of this indicator is the PDF smoothing technique, which applies a Probability Density Function to calculate a smoothed moving average. This method allows the indicator to assign adaptive weights to data points, making it responsive to market changes without overreacting to short-term volatility.
Key parameters include:
Variance: Controls the spread of the PDF weighting. A smaller variance results in sharper responses, while a larger variance smooths out the curve.
Mean: Shifts the PDF’s center, allowing traders to tweak how weights are distributed around the data points.
Smoothing Method: Offers the choice between EMA (Exponential Moving Average) and SMA (Simple Moving Average) for blending the PDF-smoothed data with traditional moving average methods.
By combining these parameters, the PDF smoothing creates a moving average that effectively captures underlying trends.
Supertrend: Adaptive Trend and Volatility Tracking
The Supertrend is a well-known volatility-based indicator that dynamically adjusts to market conditions using the ATR (Average True Range). In this script, the PDF-smoothed moving average acts as the price input, making the Supertrend calculation more adaptive and precise.
Key Supertrend Features:
ATR Period: Determines the lookback period for calculating market volatility.
Factor: Multiplies the ATR to set the distance between the Supertrend and the price. A higher factor creates wider bands, filtering out smaller price movements, while a lower factor captures tighter trends.
Dynamic Direction: The Supertrend flips its direction based on price interactions with the calculated upper and lower bands:
Uptrend : When the price is above the Supertrend, the direction turns bullish.
Downtrend : When the price is below the Supertrend, the direction turns bearish.
This combination of PDF smoothing and Supertrend calculation ensures that trends are detected with greater accuracy, while volatility filters out market noise.
Long and Short Signal Generation
The PDF-MA Supertrend generates actionable trading signals by detecting transitions in the trend direction:
Long Signal (𝕃): Triggered when the trend transitions from bearish to bullish. This is visually represented with a green triangle below the price bars.
Short Signal (𝕊): Triggered when the trend transitions from bullish to bearish. This is marked with a red triangle above the price bars.
These signals provide traders with clear entry and exit points, ensuring they can capitalize on emerging trends while avoiding false signals.
Customizable Visualization Options
The indicator offers a range of visualization settings to help traders interpret the data with ease:
Show Supertrend: Option to toggle the visibility of the Supertrend line.
Candle Coloring: Automatically colors candlesticks based on the trend direction:
Green for long trends.
Red for short trends.
Long and Short Signals (𝕃 + 𝕊): Displays long (𝕃) and short (𝕊) signals directly on the chart for quick identification of trade opportunities.
Line Color Customization: Allows users to customize the colors for long and short trends.
Alert Conditions
To ensure traders never miss an opportunity, the PDF-MA Supertrend includes built-in alerts for trend changes:
Long Signal Alert: Notifies when a bullish trend is identified.
Short Signal Alert: Notifies when a bearish trend is identified.
These alerts can be configured for real-time notifications via SMS, email, or push notifications, making it easier to stay updated on market movements.
Suggested Parameter Adjustments
The indicator’s effectiveness can be fine-tuned using the following guidelines:
Variance:
For low-volatility assets (e.g., indices): Use a smaller variance (1.0–1.5) for smoother trends.
For high-volatility assets (e.g., cryptocurrencies): Use a larger variance (1.5–2.0) to better capture rapid price changes.
ATR Factor:
A higher factor (e.g., 2.0) is better suited for long-term trend-following strategies.
A lower factor (e.g., 1.5) captures shorter-term trends.
Smoothing Period:
Shorter periods provide more reactive signals but may increase noise.
Longer periods offer stability and better alignment with significant trends.
Experimentation is encouraged to find the optimal settings for specific assets and trading strategies.
Trading Applications
The PDF-MA Supertrend is a versatile indicator suited to a variety of trading approaches:
Trend Following : Use the Supertrend line and signals to follow market trends and ride sustained price movements.
Reversal Trading : Spot potential trend reversals as the Supertrend flips direction.
Volatility Analysis : Adjust the ATR factor to filter out minor price fluctuations or capture sharp movements.
Final Thoughts
The PDF-MA Supertrend combines the precision of Probability Density Function smoothing with the adaptability of the Supertrend methodology, offering traders a powerful tool for identifying trends and volatility. With its customizable parameters, actionable signals, and built-in alerts, this indicator is an excellent choice for traders seeking a robust and reliable system for trend detection and entry/exit timing.
As always, backtesting and incorporating this indicator into a broader strategy are recommended for optimal results.
Radial Basis Kernal ATR [BackQuant]Radial Basis Kernel ATR
The Radial Basis Kernel ATR is a trading indicator that combines the classic Average True Range (ATR) with advanced Radial Basis Function (RBF) kernel smoothing . This innovative approach creates a highly adaptive and precise tool for detecting volatility, identifying trends, and providing dynamic support and resistance levels.
With its configurable parameters and ability to adjust to market conditions, this indicator offers traders a robust framework for making informed decisions across various assets and timeframes.
Key Feature: Radial Basis Function Kernel Smoothing
The Radial Basis Function (RBF) kernel is at the heart of this indicator, applying sophisticated mathematical techniques to smooth price data and calculate an enhanced version of ATR. By weighting data points dynamically, the RBF kernel ensures that recent price movements are given appropriate emphasis without overreacting to short-term noise.
The RBF kernel uses a gamma factor to control the degree of smoothing, making it highly adaptable to different asset classes and market conditions:
Gamma Factor Adjustment :
For low-volatility data (e.g., indices), a smaller gamma (0.05–0.1) ensures smoother trends and avoids overly sharp responses.
For high-volatility data (e.g., cryptocurrencies), a larger gamma (0.1–0.2) captures the increased price fluctuations while maintaining stability.
Experimentation is Key : Traders are encouraged to backtest and visually compare different gamma values to find the optimal setting for their specific asset and strategy.
The gamma factor dynamically adjusts based on the variance of the source data, ensuring the indicator remains effective across a wide range of market conditions.
Average True Range (ATR) with Dynamic Bands
The ATR is a widely used volatility measure that captures the degree of price movement over a specific period. This indicator enhances the traditional ATR by integrating the RBF kernel, resulting in a smoothed and adaptive ATR calculation.
Dynamic bands are created around the RBF kernel output using a user-defined ATR factor , offering valuable insights into potential support and resistance zones. These bands expand and contract based on market volatility, providing a visual representation of potential price movement.
Moving Average Confluence
For additional confirmation, the indicator includes the option to overlay a moving average on the smoothed ATR. Traders can choose from several moving average types, such as EMA , SMA , or Hull , and adjust the lookback period to suit their strategy. This feature helps identify broader trends and potential confluence areas, making the indicator even more versatile.
Long and Short Trend Detection
The indicator provides long and short signals based on the directional movement of the smoothed ATR:
Long Signal : Triggered when the ATR crosses above its previous value, indicating bullish momentum.
Short Signal : Triggered when the ATR crosses below its previous value, signaling bearish momentum.
These trend signals are visually highlighted on the chart with green and red bar coloring (optional), providing clear and actionable insights.
Customization Options
The Radial Basis Kernel ATR offers extensive customization options, allowing traders to tailor the indicator to their preferences:
RBF Kernel Settings
Source : Select the price data (e.g., close, high, low) used for the kernel calculation.
Kernel Length : Define the lookback period for the RBF kernel, controlling the smoothing effect.
Gamma Factor : Adjust the smoothing sensitivity, with smaller values for smoother trends and larger values for responsiveness.
ATR Settings
ATR Period : Set the period for ATR calculation, with shorter periods capturing more short-term volatility and longer periods providing a broader view.
ATR Factor : Adjust the scaling of ATR bands for dynamic support and resistance levels.
Confluence Settings
Moving Average Type : Choose from various moving average types for additional trend confirmation.
Moving Average Period : Define the lookback period for the moving average overlay.
Visualization
Trend Coloring : Enable or disable bar coloring based on trend direction (green for long, red for short).
Background Highlighting : Add optional background shading to emphasize long and short trends visually.
Line Width : Customize the thickness of the plotted ATR line for better visibility.
Alerts and Automation
To help traders stay on top of market movements, the indicator includes built-in alerts for trend changes:
Kernel ATR Trend Up : Triggered when the ATR indicates a bullish trend.
Kernel ATR Trend Down : Triggered when the ATR signals a bearish trend.
These alerts ensure traders never miss important opportunities, providing timely notifications directly to their preferred device.
Suggested Gamma Values
The effectiveness of the gamma factor depends on the asset type and the selected kernel length:
Low Volatility Assets (e.g., indices): Use a smaller gamma factor (approximately 0.05–0.1) for smoother trends.
High Volatility Assets (e.g., crypto): Use a larger gamma factor (approximately 0.1–0.2) to capture sharper price movements.
Experimentation : Fine-tune the gamma factor using backtests or visual comparisons to optimize for specific assets and strategies.
Trading Applications
The Radial Basis Kernel ATR is a versatile tool suitable for various trading styles and strategies:
Trend Following : Use the smoothed ATR and dynamic bands to identify and follow trends with confidence.
Reversal Trading : Spot potential reversals by observing interactions with dynamic ATR bands and moving average confluence.
Volatility Analysis : Analyze market volatility to adjust risk management strategies or position sizing.
Final Thoughts
The Radial Basis Kernel ATR combines advanced mathematical techniques with the practical utility of ATR, offering traders a powerful and adaptive tool for volatility analysis and trend detection. Its ability to dynamically adjust to market conditions through the RBF kernel and gamma factor makes it a unique and indispensable part of any trader's toolkit.
By combining sophisticated smoothing , dynamic bands , and customizable visualization , this indicator enhances the ability to read market conditions and make more informed trading decisions. As always, backtesting and incorporating it into a broader strategy are recommended for optimal results.
PDF MA For Loop [BackQuant]PDF MA For Loop
Introducing the PDF MA For Loop, an innovative trading indicator that combines Probability Density Function (PDF) smoothing with a dynamic for-loop scoring mechanism. This advanced tool provides traders with precise trend-following signals, helping to identify long and short opportunities with improved clarity and adaptability to market conditions.
If you would like to check out the stand alone PDF Moving Average:
Core Concept: Probability Density Function (PDF) Smoothing
The PDF smoothing method is a unique approach that applies adaptive weights to price data based on a Probability Density Function. This ensures that recent data points receive appropriate emphasis while maintaining a smooth transition across the data set. The result is a moving average that is not only smoother but also more responsive to market changes.
Key parameters in PDF smoothing:
Variance : Controls the spread of the PDF, where a higher value results in broader smoothing and a lower value makes the moving average more sensitive.
Mean : Centers the PDF around a specific value, influencing the weighting and responsiveness of the smoothing process.
By combining PDF smoothing with traditional moving averages (EMA or SMA), the indicator creates a hybrid signal that balances responsiveness and reliability.
For-Loop Scoring Mechanism
At the heart of this indicator is the for-loop scoring mechanism, which evaluates the smoothed PDF moving average over a defined range of historical data points. This process assigns a score to the current market condition based on whether the PDF moving average is greater than or less than previous values.
Long Signal: A long signal is generated when the score exceeds the Long Threshold (default set at 40), indicating upward momentum.
Short Signal: A short signal is triggered when the score crosses below the Short Threshold (default set at -10), suggesting potential downward momentum.
This dynamic scoring system ensures that the indicator remains adaptive, capturing trends and shifts in market sentiment effectively.
Customization Options
The PDF MA For Loop includes a variety of customizable settings to fit different trading styles and strategies:
Calculation Settings
Price Source : Select the input price for the calculation (default is the close price).
Smoothing Method : Choose between EMA or SMA for the additional smoothing layer, providing flexibility to adapt to market conditions.
Smoothing Period : Adjust the lookback period for the smoothing function, with shorter periods providing more sensitivity and longer periods offering greater stability.
Variance & Mean : Fine-tune the PDF function parameters to control the weighting of the smoothing process.
Signal Settings
Thresholds : Customize the upper and lower thresholds to define the sensitivity of the long and short signals.
For Loop Range : Set the range of historical data points analyzed by the for-loop, influencing the depth of the scoring mechanism.
UI Settings
Signal Line Width: Adjust the thickness of the plotted signal line for better visibility.
Candle Coloring: Enable or disable the coloring of candlesticks based on trend direction (green for long, red for short, gray for neutral).
Background Coloring: Add background shading to highlight long and short signals for an enhanced visual experience.
Alerts and Automation
The indicator includes built-in alert conditions to notify traders of important market events:
Long Signal Alert: Notifies when the score exceeds the upper threshold, indicating a bullish trend.
Short Signal Alert: Notifies when the score crosses below the lower threshold, signaling a bearish trend.
These alerts can be configured for real-time notifications, allowing traders to respond quickly to market changes without constant chart monitoring.
Trading Applications
The PDF MA For Loop is versatile and can be applied across various trading strategies and market conditions:
Trend Following: The PDF smoothing method combined with for-loop scoring makes this indicator particularly effective for identifying and following trends.
Reversal Trading: By observing the thresholds and score, traders can anticipate potential reversals when the trend shifts from long to short (or vice versa).
Risk Management: The dynamic thresholds and scoring provide clear signals, allowing traders to enter and exit trades with greater confidence and precision.
Final Thoughts
The PDF MA For Loopis merges advanced mathematical concepts with practical trading tools. By leveraging Probability Density Function smoothing and a dynamic for-loop scoring system, it provides traders with clear, actionable signals while adapting to market conditions.
Whether you’re looking for an edge in trend-following strategies or seeking precision in identifying reversals, this indicator offers the flexibility and power to enhance your trading decisions
As always, backtesting and integrating the PDF MA For Loop into a comprehensive trading strategy is recommended for optimal performance, as no single indicator should be used in isolation.
Thus following all of the key points here are some sample backtests on the 1D Chart
Disclaimer: Backtests are based off past results, and are not indicative of the future.
INDEX:BTCUSD
INDEX:ETHUSD
BINANCE:SOLUSD
Alternate Bat Harmonic Pattern [TradingFinder] ALT Bat Indicator🔵 Introduction
The Alternate Bat harmonic pattern is one of the most precise and practical tools in technical analysis, introduced by Scott Carney in 2003. This pattern focuses on specific Fibonacci ratios, such as 0.382 at point B and 1.13XA at point D, to identify Potential Reversal Zones (PRZ) where price is likely to reverse.
The Alternative Bat pattern emerged as a result of repeated failures observed in the standard Bat pattern. Traders entering trades near the 0.886XA level of the standard Bat often encountered losses. In the Alternate Bat, point D extends beyond 0.886XA, typically reversing at 1.13XA, offering a more accurate identification of the reversal zone.
A key characteristic of this pattern is its M- or W-shaped structure, where the midpoint B retraces 0.382XA or less. Additionally, the CD leg requires an extension of 2.0 to 3.618 to complete the pattern. Due to its accuracy and the predictable behavior of price near the PRZ, the Alternate Bat pattern is recognized as a powerful tool for forecasting price reversals.
In the bullish Alternative Bat pattern, an M-shaped structure forms. After an initial upward movement (XA), price undergoes a short correction at point B (0.382XA) and then declines toward point D (1.13XA and an extension of 2.0 to 3.618BC), where a potential upward reversal is expected.
In the bearish Alternate Bat pattern, a W-shaped structure forms. After an initial downward movement (XA), price retraces slightly at point B (0.382XA) and then rises toward point D (1.13XA and an extension of 2.0 to 3.618BC), where a potential downward reversal is anticipated.
🔵 How to Use
The Alternate Bat harmonic pattern is a key tool for identifying potential reversal zones (PRZ) in the market. By leveraging the 0.382 retracement at point B and the 1.13XA extension at point D, along with symmetrical price structures, this pattern offers precise reversal opportunities in both bullish and bearish market conditions.
🟣 Bullish Alternate Bat Pattern
The bullish Alternate Bat pattern forms during a downtrend, signaling a potential reversal to the upside. This pattern consists of three downward movements with two corrective waves, ultimately reaching point D, which marks the PRZ.
At the PRZ, the convergence of Fibonacci levels—1.13XA and extensions ranging from 2.0 to 3.618BC—creates a strong support zone where price is likely to reverse upward.
🟣 Bearish Alternative Bat Pattern
The bearish Alternate Bat pattern develops during an uptrend, indicating a potential reversal to the downside. This pattern features three upward price movements with two retracements, ending at point D, where the PRZ forms.
Point D is defined by the 1.13XA extension and the 2.0 to 3.618BC projection, creating a strong resistance zone where price is expected to reverse downward.
🔵 Setting
🟣 Logical Setting
ZigZag Pivot Period : You can adjust the period so that the harmonic patterns are adjusted according to the pivot period you want. This factor is the most important parameter in pattern recognition.
Show Valid Format : If this parameter is on "On" mode, only patterns will be displayed that they have exact format and no noise can be seen in them. If "Off" is, the patterns displayed that maybe are noisy and do not exactly correspond to the original pattern.
Show Formation Last Pivot Confirm : if Turned on, you can see this ability of patterns when their last pivot is formed. If this feature is off, it will see the patterns as soon as they are formed. The advantage of this option being clear is less formation of fielded patterns, and it is accompanied by the latest pattern seeing and a sharp reduction in reward to risk.
Period of Formation Last Pivot : Using this parameter you can determine that the last pivot is based on Pivot period.
🟣 Genaral Setting
Show : Enter "On" to display the template and "Off" to not display the template.
Color : Enter the desired color to draw the pattern in this parameter.
LineWidth : You can enter the number 1 or numbers higher than one to adjust the thickness of the drawing lines. This number must be an integer and increases with increasing thickness.
LabelSize : You can adjust the size of the labels by using the "size.auto", "size.tiny", "size.smal", "size.normal", "size.large" or "size.huge" entries.
🟣 Alert Setting
Alert : On / Off
Message Frequency : This string parameter defines the announcement frequency. Choices include: "All" (activates the alert every time the function is called), "Once Per Bar" (activates the alert only on the first call within the bar), and "Once Per Bar Close" (the alert is activated only by a call at the last script execution of the real-time bar upon closing). The default setting is "Once per Bar".
Show Alert Time by Time Zone : The date, hour, and minute you receive in alert messages can be based on any time zone you choose. For example, if you want New York time, you should enter "UTC-4". This input is set to the time zone "UTC" by default.
🔵 Conclusion
The Alternate Bat harmonic pattern, with its precise Fibonacci ratios like 0.382 and 1.13XA, is a reliable tool for identifying Potential Reversal Zones (PRZ) in financial markets. By recognizing symmetrical price structures and focusing on both bullish and bearish scenarios, traders can identify optimal entry and exit points with high accuracy.
The key strength of this pattern lies in its ability to define strong support and resistance zones near the PRZ, increasing the probability of price reversals. Combining the pattern with candlestick confirmations and volume analysis enhances its effectiveness.
Ultimately, incorporating the Alternative Bat pattern with proper risk management and Fibonacci-based targets allows traders to enter the market confidently and capitalize on potential price reversals.
Machine Learning RSI [BackQuant]Machine Learning RSI
The Machine Learning RSI is a cutting-edge trading indicator that combines the power of Relative Strength Index (RSI) with Machine Learning (ML) clustering techniques to dynamically determine overbought and oversold thresholds. This advanced indicator adapts to market conditions in real-time, offering traders a robust tool for identifying optimal entry and exit points with increased precision.
Core Concept: Relative Strength Index (RSI)
The RSI is a well-known momentum oscillator that measures the speed and change of price movements, oscillating between 0 and 100. Typically, RSI values above 70 are considered overbought, and values below 30 are considered oversold. However, static thresholds may not be effective in all market conditions.
This script enhances the RSI by integrating a dynamic thresholding system powered by Machine Learning clustering, allowing it to adapt thresholds based on historical RSI behavior and market context.
Machine Learning Clustering for Dynamic Thresholds
The Machine Learning (ML) component uses clustering to calculate dynamic thresholds for overbought and oversold levels. Instead of relying on fixed RSI levels, this indicator clusters historical RSI values into three groups using a percentile-based initialization and iterative optimization:
Cluster 1: Represents lower RSI values (typically associated with oversold conditions).
Cluster 2: Represents mid-range RSI values.
Cluster 3: Represents higher RSI values (typically associated with overbought conditions).
Dynamic thresholds are determined as follows:
Long Threshold: The upper centroid value of Cluster 3.
Short Threshold: The lower centroid value of Cluster 1.
This approach ensures that the indicator adapts to the current market regime, providing more accurate signals in volatile or trending conditions.
Smoothing Options for RSI
To further enhance the effectiveness of the RSI, this script allows traders to apply various smoothing methods to the RSI calculation, including:
Simple Moving Average (SMA)
Exponential Moving Average (EMA)
Weighted Moving Average (WMA)
Hull Moving Average (HMA)
Linear Regression (LINREG)
Double Exponential Moving Average (DEMA)
Triple Exponential Moving Average (TEMA)
Adaptive Linear Moving Average (ALMA)
T3 Moving Average
Traders can select their preferred smoothing method and adjust the smoothing period to suit their trading style and market conditions. The option to smooth the RSI reduces noise and makes the indicator more reliable for detecting trends and reversals.
Long and Short Signals
The indicator generates long and short signals based on the relationship between the RSI value and the dynamic thresholds:
Long Signals: Triggered when the RSI crosses above the long threshold, signaling bullish momentum.
Short Signals: Triggered when the RSI falls below the short threshold, signaling bearish momentum.
These signals are dynamically adjusted to reflect real-time market conditions, making them more robust than static RSI signals.
Visualization and Clustering Insights
The Machine Learning RSI provides an intuitive and visually rich interface, including:
RSI Line: Plotted in real-time, color-coded based on its position relative to the dynamic thresholds (green for long, red for short, gray for neutral).
Dynamic Threshold Lines: The script plots the long and short thresholds calculated by the ML clustering process, providing a clear visual reference for overbought and oversold levels.
Cluster Plots: Each RSI cluster is displayed with distinct colors (green, orange, and red) to give traders insights into how RSI values are grouped and how the dynamic thresholds are derived.
Customization Options
The Machine Learning RSI is highly customizable, allowing traders to tailor the indicator to their preferences:
RSI Settings : Adjust the RSI length, source price, and smoothing method to match your trading strategy.
Threshold Settings : Define the range and step size for clustering thresholds, allowing you to fine-tune the clustering process.
Optimization Settings : Control the performance memory, maximum clustering steps, and maximum data points for ML calculations to ensure optimal performance.
UI Settings : Customize the appearance of the RSI plot, dynamic thresholds, and cluster plots. Traders can also enable or disable candle coloring based on trend direction.
Alerts and Automation
To assist traders in staying on top of market movements, the script includes alert conditions for key events:
Long Signal: When the RSI crosses above the long threshold.
Short Signal: When the RSI crosses below the short threshold.
These alerts can be configured to notify traders in real-time, enabling timely decisions without constant chart monitoring.
Trading Applications
The Machine Learning RSI is versatile and can be applied to various trading strategies, including:
Trend Following: By dynamically adjusting thresholds, this indicator is effective in identifying and following trends in real-time.
Reversal Trading: The ML clustering process helps identify extreme RSI levels, offering reliable signals for reversals.
Range-Bound Trading: The dynamic thresholds adapt to market conditions, making the indicator suitable for trading in sideways markets where static thresholds often fail.
Final Thoughts
The Machine Learning RSI represents a significant advancement in RSI-based trading indicators. By integrating Machine Learning clustering techniques, this script overcomes the limitations of static thresholds, providing dynamic, adaptive signals that respond to market conditions in real-time. With its robust visualization, customizable settings, and alert capabilities, this indicator is a powerful tool for traders seeking to enhance their momentum analysis and improve decision-making.
As always, thorough backtesting and integration into a broader trading strategy are recommended to maximize the effectiveness!
PDF Smoothed Moving Average [BackQuant]PDF Smoothed Moving Average
Introducing BackQuant’s PDF Smoothed Moving Average (PDF-MA) — an innovative trading indicator that applies Probability Density Function (PDF) weighting to moving averages, creating a unique, trend-following tool that offers adaptive smoothing to price movements. This advanced indicator gives traders an edge by blending PDF-weighted values with conventional moving averages, helping to capture trend shifts with enhanced clarity.
Core Concept: Probability Density Function (PDF) Smoothing
The Probability Density Function (PDF) provides a mathematical approach to applying adaptive weighting to data points based on a specified variance and mean. In the PDF-MA indicator, the PDF function is used to weight price data, adding a layer of probabilistic smoothing that enhances the detection of trend strength while reducing noise.
The PDF weights are controlled by two key parameters:
Variance: Determines the spread of the weights, where higher values spread out the weighting effect, providing broader smoothing.
Mean : Centers the weights around a particular price value, influencing the trend’s directionality and sensitivity.
These PDF weights are applied to each price point over the chosen period, creating an adaptive and smooth moving average that more closely reflects the underlying price trend.
Blending PDF with Standard Moving Averages
To further improve the PDF-MA, this indicator combines the PDF-weighted average with a traditional moving average, selected by the user as either an Exponential Moving Average (EMA) or Simple Moving Average (SMA). This blended approach leverages the strengths of each method: the responsiveness of PDF smoothing and the robustness of conventional moving averages.
Smoothing Method: Traders can choose between EMA and SMA for the additional moving average layer. The EMA is more responsive to recent prices, while the SMA provides a consistent average across the selected period.
Smoothing Period: Controls the length of the lookback period, affecting how sensitive the average is to price changes.
The result is a PDF-MA that provides a reliable trend line, reflecting both the PDF weighting and traditional moving average values, ideal for use in trend-following and momentum-based strategies.
Trend Detection and Candle Coloring
The PDF-MA includes a built-in trend detection feature that dynamically colors candles based on the direction of the smoothed moving average:
Uptrend: When the PDF-MA value is increasing, the trend is considered bullish, and candles are colored green, indicating potential buying conditions.
Downtrend: When the PDF-MA value is decreasing, the trend is considered bearish, and candles are colored red, signaling potential selling or shorting conditions.
These color-coded candles provide a quick visual reference for the trend direction, helping traders make real-time decisions based on the current market trend.
Customization and Visualization Options
This indicator offers a range of customization options, allowing traders to tailor it to their specific preferences and trading environment:
Price Source : Choose the price data for calculation, with options like close, open, high, low, or HLC3.
Variance and Mean : Fine-tune the PDF weighting parameters to control the indicator’s sensitivity and responsiveness to price data.
Smoothing Method : Select either EMA or SMA to customize the conventional moving average layer used in conjunction with the PDF.
Smoothing Period : Set the lookback period for the moving average, with a longer period providing more stability and a shorter period offering greater sensitivity.
Candle Coloring : Enable or disable candle coloring based on trend direction, providing additional clarity in identifying bullish and bearish phases.
Trading Applications
The PDF Smoothed Moving Average can be applied across various trading strategies and timeframes:
Trend Following : By smoothing price data with PDF weighting, this indicator helps traders identify long-term trends while filtering out short-term noise.
Reversal Trading : The PDF-MA’s trend coloring feature can help pinpoint potential reversal points by showing shifts in the trend direction, allowing traders to enter or exit positions at optimal moments.
Swing Trading : The PDF-MA provides a clear trend line that swing traders can use to capture intermediate price moves, following the trend direction until it shifts.
Final Thoughts
The PDF Smoothed Moving Average is a highly adaptable indicator that combines probabilistic smoothing with traditional moving averages, providing a nuanced view of market trends. By integrating PDF-based weighting with the flexibility of EMA or SMA smoothing, this indicator offers traders an advanced tool for trend analysis that adapts to changing market conditions with reduced lag and increased accuracy.
Whether you’re trading trends, reversals, or swings, the PDF-MA offers valuable insights into the direction and strength of price movements, making it a versatile addition to any trading strategy.
Mini ChartDescription:
The indicator displays a mini candlestick chart as a table. You can add up to 3 such charts and use different assets / timeframes in any of them. Each chart can have a max of 15-20 candles (depending on the settings). You can customise the colors and styles, including price scale, grid and a volume chart. If you hover on any displayed candle, you will see price and volume info for that candle. The candles can also be highlighted based on price or volume. The indicator can display data from both higher and lower timeframes, but is not updating very quickly if you display too many candles.
Inputs:
Each mini chart has inputs for:
- Number of candles
- Timeframe
- Asset
- Table position
- Table height
- Grid resolution
- Left and Right price scales
- Candle highlighting (which can be based on Min/Max price, Min/Max Volume, Rising/Falling Volume)
- And a checkbox for displaying volume chart below the candles
Below those inputs you have inputs for customising all the mini charts with the following:
- Header and Footer info
- Colors and styles of the charts, candles and price scales
- Sizing and spacing of the candles
- Height of the volume chart and padding of the price chart
Note:
The indicator utilises "table" objects. The limit of table cells for a chart is 10,000. Thus, the more candles you display in the mini charts, the more laggy the indicator will feel, and at some point you may surpass the 10,000 cells limit, at which point you're going to get an error.
The indicator might not update very quickly, especially if you're using data from lower timeframes.
Savitzky-Golay Z-Score [BackQuant]Savitzky-Golay Z-Score
The Savitzky-Golay Z-Score is a powerful trading indicator that combines the precision of the Savitzky-Golay filter with the statistical strength of the Z-Score. This advanced indicator is designed to detect trend shifts, identify overbought or oversold conditions, and highlight potential divergences in the market, providing traders with a unique edge in detecting momentum changes and trend reversals.
Core Concept: Savitzky-Golay Filter
The Savitzky-Golay filter is a widely-used smoothing technique that preserves important signal features such as peak detection while filtering out noise. In this indicator, the filter is applied to price data (default set to HLC3) to smooth out volatility and produce a cleaner trend line. By specifying the window size and polynomial degree, traders can fine-tune the degree of smoothing to match their preferred trading style or market conditions.
Z-Score: Measuring Deviation
The Z-Score is a statistical measure that indicates how far the current price is from its mean in terms of standard deviations. In trading, the Z-Score can be used to identify extreme price moves that are likely to revert or continue trending. A positive Z-Score means the price is above the mean, while a negative Z-Score indicates the price is below the mean.
This script calculates the Z-Score based on the Savitzky-Golay filtered price, enabling traders to detect moments when the price is diverging from its typical range and may present an opportunity for a trade.
Long and Short Conditions
The Savitzky-Golay Z-Score generates clear long and short signals based on the Z-Score value:
Long Signals : When the Z-Score is positive, indicating the price is above its smoothed mean, a long signal is generated. The color of the bars turns green, signaling upward momentum.
Short Signals : When the Z-Score is negative, indicating the price is below its smoothed mean, a short signal is generated. The bars turn red, signaling downward momentum.
These signals allow traders to follow the prevailing trend with confidence, using statistical backing to avoid false signals from short-term volatility.
Standard Deviation Levels and Extreme Levels
This indicator includes several features to help visualize overbought and oversold conditions:
Standard Deviation Levels: The script plots horizontal lines at +1, +2, -1, and -2 standard deviations. These levels provide a reference for how far the current price is from the mean, allowing traders to quickly identify when the price is moving into extreme territory.
Extreme Levels: Additional extreme levels at +3 and +4 (and their negative counterparts) are plotted to highlight areas where the price is highly likely to revert. These extreme levels provide important insight into market conditions that are far outside the norm, signaling caution or potential reversal zones.
The indicator also adapts the color shading of these extreme zones based on the Z-Score’s strength. For example, the area between +3 and +4 is shaded with a stronger color when the Z-Score approaches these values, giving a visual representation of market pressure.
Divergences: Detecting Hidden and Regular Signals
A key feature of the Savitzky-Golay Z-Score is its ability to detect bullish and bearish divergences, both regular and hidden:
Regular Bullish Divergence: This occurs when the price makes a lower low while the Z-Score forms a higher low. It signals that bearish momentum is weakening, and a bullish reversal could be near.
Hidden Bullish Divergence: This divergence occurs when the price makes a higher low while the Z-Score forms a lower low. It signals that bullish momentum may continue after a temporary pullback.
Regular Bearish Divergence: This occurs when the price makes a higher high while the Z-Score forms a lower high, signaling that bullish momentum is weakening and a bearish reversal may be near.
Hidden Bearish Divergence: This divergence occurs when the price makes a lower high while the Z-Score forms a higher high, indicating that bearish momentum may continue after a temporary rally.
These divergences are plotted directly on the chart, making it easier for traders to spot when the price and momentum are out of sync and when a potential reversal may occur.
Customization and Visualization
The Savitzky-Golay Z-Score offers a range of customization options to fit different trading styles:
Window Size and Polynomial Degree: Adjust the window size and polynomial degree of the Savitzky-Golay filter to control how much smoothing is applied to the price data.
Z-Score Lookback Period: Set the lookback period for calculating the Z-Score, allowing traders to fine-tune the sensitivity to short-term or long-term price movements.
Display Options: Choose whether to display standard deviation levels, extreme levels, and divergence labels on the chart.
Bar Color: Color the price bars based on trend direction, with green for bullish trends and red for bearish trends, allowing traders to easily visualize the current momentum.
Divergences: Enable or disable divergence detection, and adjust the lookback periods for pivots used to detect regular and hidden divergences.
Alerts and Automation
To ensure you never miss an important signal, the indicator includes built-in alert conditions for the following events:
Positive Z-Score (Long Signal): Triggers an alert when the Z-Score crosses above zero, indicating a potential buying opportunity.
Negative Z-Score (Short Signal): Triggers an alert when the Z-Score crosses below zero, signaling a potential short opportunity.
Shifting Momentum: Alerts when the Z-Score is shifting up or down, providing early warning of changing market conditions.
These alerts can be configured to notify you via email, SMS, or app notification, allowing you to stay on top of the market without having to constantly monitor the chart.
Trading Applications
The Savitzky-Golay Z-Score is a versatile tool that can be applied across multiple trading strategies:
Trend Following: By smoothing the price and calculating the Z-Score, this indicator helps traders follow the prevailing trend while avoiding false signals from short-term volatility.
Mean Reversion: The Z-Score highlights moments when the price is far from its mean, helping traders identify overbought or oversold conditions and capitalize on potential reversals.
Divergence Trading: Regular and hidden divergences between the Z-Score and price provide early warning of trend reversals, allowing traders to enter trades at opportune moments.
Final Thoughts
The Savitzky-Golay Z-Score is an advanced statistical tool designed to provide a clearer view of market trends and momentum. By applying the Savitzky-Golay filter and Z-Score analysis, this indicator reduces noise and highlights key areas where the market may reverse or accelerate, giving traders a significant edge in understanding price behavior.
Whether you’re a trend follower or a reversal trader, this indicator offers the flexibility and insights you need to navigate complex markets with confidence.
Majors Rotation System [BackQuant]Majors Rotation System
Introducing BackQuant's Majors Rotation System, a comprehensive portfolio management tool for rotating among the major cryptocurrencies—BTC, ETH, and SOL. This system is designed to optimize returns by selecting the strongest-performing asset while avoiding periods of market weakness. It employs a long and cash-only strategy, meaning the system will only hold positions when market conditions are favorable, and will stay in cash during downtrends. Additionally, it incorporates a powerful regime filter to ensure the system is inactive during market-wide downturns.
This script is ideal for crypto traders looking to improve performance by dynamically allocating capital based on real-time performance metrics, rather than relying on a simple buy-and-hold strategy.
Key Features
Dynamic Asset Rotation: The system constantly evaluates the performance of BTC, ETH, and SOL, selecting the strongest asset based on a ratio matrix. This matrix compares the relative strength of each asset to one another, ensuring that your portfolio is always positioned in the cryptocurrency with the most momentum.
Long and Cash-Only Portfolio: This system only takes long positions or remains in cash. By avoiding short positions, it reduces exposure during market downturns. The built-in regime filter ensures the system only operates when the broader market (represented by the TOTAL crypto market cap) is trending up, offering additional protection against unfavorable market conditions.
Equity Tracking: The script provides a real-time visualization of portfolio equity compared to a buy-and-hold strategy. It displays the equity curve of the portfolio while allowing you to compare it against the hypothetical equity of holding BTC, ETH, or SOL individually (Buy and Hold).
Performance Metrics: In addition to equity visualization, the system provides detailed performance metrics, including:
Sharpe Ratio: Measures risk-adjusted returns.
Sortino Ratio: Focuses on downside risk.
Omega Ratio: Evaluates returns relative to risk.
Maximum Drawdown: The maximum observed loss from a peak to a trough.
These metrics allow traders to assess the efficiency of the rotation system compared to simply holding assets.
Visual Cues:
Painted Candles: The script provides a visual trend indicator by painting candles according to the trend of the selected chart, helping traders quickly identify momentum shifts.
Support for Multiple Assets: The system allows users to toggle between BTC, ETH, and SOL or view the entire portfolio at once. It displays key metrics for each asset and offers an intuitive way to understand which asset is currently outperforming.
Regime Filter: A key aspect of this system is the regime filter, which only allows trading in favorable market conditions. It uses a Universal TPI (Trend Performance Indicator) to evaluate whether the overall crypto market (TOTAL Market Cap) and key assets (BTC, ETH) are in a bullish trend. If the market is in a downtrend, the system will exit positions and move into cash.
Customizable Parameters: Users can customize several important aspects of the system:
Starting Date: Choose when the backtest or live trading begins.
Starting Capital: Set the initial capital for backtesting purposes.
Visualization Options: Toggle between base data, ratioed data, and equity plots. Users can also customize the line width and color settings for better chart clarity.
Adaptive Momentum Scoring: The system uses advanced indicators, which are not disclosed (proprietary) to assess the trend and momentum of the selected cryptocurrencies dynamically.
How the Rotation Works
The system uses a universal algorithm to calculate trend and momentum signals for BTC, ETH, and SOL. These signals are processed through a ratio matrix, which compares the performance of each asset against the others. Based on this comparison, the system identifies the strongest asset and allocates capital accordingly.
BTC, ETH, and SOL Scores: These scores represent the relative strength of each asset based on the universal algorithm. The system dynamically selects the asset with the highest score, rotating out of underperforming assets and into the top performer.
Allocation Decisions: The system determines whether to allocate capital to BTC, ETH, SOL, or Cash based on the scores. If none of the assets show strength, the system defaults to cash to protect the portfolio from market downturns.
Equity and Buy-and-Hold Comparisons
This script provides a side-by-side comparison of the portfolio’s equity curve and a buy-and-hold strategy:
Portfolio Equity: Shows the performance of the system as it rotates between BTC, ETH, and SOL.
Buy-and-Hold Equity: Displays how the portfolio would have performed if you simply held BTC, ETH, or SOL without trading.
These comparisons allow traders to see how the dynamic rotation system performs relative to a passive holding strategy.
Alerts and Visual Feedback
The system provides real-time alerts when asset allocations change, notifying traders when the system moves capital between assets or into cash. Additionally, the system offers detailed visual feedback, including:
Equity Curve Plots: Displays the equity curve of the portfolio and the individual assets.
Score Labels: Shows the strength scores for BTC, ETH, and SOL directly on the chart for easy monitoring.
Final Thoughts
The Majors Rotation System offers a powerful way to navigate the highly volatile crypto market by rotating between the strongest performing assets and staying in cash when conditions are unfavorable. With its advanced metrics, equity tracking, and built-in regime filter, this system is designed to optimize returns while minimizing risk.
Savitzky Golay Median Filtered RSI [BackQuant]Savitzky Golay Median Filtered RSI
Introducing BackQuant's Savitzky Golay Median Filtered RSI, a cutting-edge indicator that enhances the classic Relative Strength Index (RSI) by applying both a Savitzky-Golay filter and a median filter to provide smoother and more reliable signals. This advanced approach helps reduce noise and captures true momentum trends with greater precision. Let’s break down how the indicator works, the features it offers, and how it can improve your trading strategy.
Core Concept: Relative Strength Index (RSI)
The Relative Strength Index (RSI) is a widely used momentum oscillator that measures the speed and change of price movements. It oscillates between 0 and 100, with levels above 70 typically indicating overbought conditions and levels below 30 indicating oversold conditions. However, the standard RSI can sometimes generate noisy signals, especially in volatile markets, making it challenging to identify reliable entry and exit points.
To improve upon the traditional RSI, this indicator introduces two powerful filters: the Savitzky-Golay filter and a median filter.
Savitzky-Golay Filter: Smoothing with Precision
The Savitzky-Golay filter is a digital filtering technique used to smooth data while preserving important features, such as peaks and trends. Unlike simple moving averages that can distort important price data, the Savitzky-Golay filter uses polynomial regression to fit the data, providing a more accurate and less lagging result.
In this script, the Savitzky-Golay filter is applied to the RSI values to smooth out short-term fluctuations and provide a more reliable signal. By using a window size of 5 and a polynomial degree of 2, the filter effectively reduces noise without compromising the integrity of the underlying price movements.
Median Filter: Reducing Outliers
After applying the Savitzky-Golay filter, the median filter is applied to the smoothed RSI values. The median filter is particularly effective at removing short-lived outliers, further enhancing the accuracy of the RSI by reducing the impact of sudden and temporary price spikes or drops. This combination of filters creates an ultra-smooth RSI that is better suited for detecting true market trends.
Long and Short Signals
The Savitzky Golay Median Filtered RSI generates long and short signals based on user-defined threshold levels:
Long Signals: A long signal is triggered when the filtered RSI exceeds the Long Threshold (default set at 176). This indicates that momentum is shifting upward, and it may present a good buying opportunity.
Short Signals: A short signal is generated when the filtered RSI falls below the Short Threshold (default set at 162). This suggests that momentum is weakening, potentially signaling a selling opportunity or exit from a long position.
These threshold levels can be adjusted to suit different market conditions and timeframes, allowing traders to fine-tune the sensitivity of the indicator.
Customization and Visualization Options
The Savitzky Golay Median Filtered RSI comes with several customization options, enabling traders to tailor the indicator to their specific needs:
Calculation Source: Select the price source for the RSI calculation (default is OHLC4, but it can be changed to close, open, high, or low prices).
RSI Period: Adjust the lookback period for the RSI calculation (default is 14).
Median Filter Length: Control the length of the median filter applied to the smoothed RSI, affecting how much noise is removed from the signal.
Threshold Levels: Customize the long and short thresholds to define the sensitivity for generating buy and sell signals.
UI Settings: Choose whether to display the RSI and thresholds on the chart, color the bars according to trend direction, and adjust the line width and colors used for long and short signals.
Visual Feedback: Color-Coded Signals and Thresholds
To make the signals easier to interpret, the indicator offers visual feedback by coloring the price bars and the RSI plot according to the current market trend:
Green Bars indicate long signals when momentum is bullish.
Red Bars indicate short signals when momentum is bearish.
Gray Bars indicate neutral or undecided conditions when no clear signal is present.
In addition, the Long and Short Thresholds can be plotted directly on the chart to provide a clear reference for when signals are triggered, allowing traders to visually gauge the strength of the RSI relative to its thresholds.
Alerts for Automation
For traders who prefer automated notifications, the Savitzky Golay Median Filtered RSI includes built-in alert conditions for long and short signals. You can configure these alerts to notify you when a buy or sell condition is met, ensuring you never miss a trading opportunity.
Trading Applications
This indicator is versatile and can be used in a variety of trading strategies:
Trend Following: The combination of Savitzky-Golay and median filtering makes this RSI particularly useful for identifying strong trends without being misled by short-term noise. Traders can use the long and short signals to enter trades in the direction of the prevailing trend.
Reversal Trading: By adjusting the threshold levels, traders can use this indicator to spot potential reversals. When the RSI moves from overbought to oversold levels (or vice versa), it may signal a shift in market direction.
Swing Trading: The smoothed RSI provides a clear signal for short to medium-term price movements, making it an excellent tool for swing traders looking to capitalize on momentum shifts.
Risk Management: The filtered RSI can be used as part of a broader risk management strategy, helping traders avoid false signals and stay in trades only when the momentum is strong.
Final Thoughts
The Savitzky Golay Median Filtered RSI takes the classic RSI to the next level by applying advanced smoothing techniques that reduce noise and improve signal reliability. Whether you’re a trend follower, swing trader, or reversal trader, this indicator provides a more refined approach to momentum analysis, helping you make better-informed trading decisions.
As with all indicators, it is important to backtest thoroughly and incorporate sound risk management strategies when using the Savitzky Golay Median Filtered RSI in your trading system.
Thus following all of the key points here are some sample backtests on the 1D Chart
Disclaimer: Backtests are based off past results, and are not indicative of the future.
INDEX:BTCUSD
INDEX:ETHUSD
BINANCE:SOLUSD
Kalman For Loop [BackQuant]Kalman For Loop
Introducing BackQuant's Kalman For Loop (Kalman FL) — a highly adaptive trading indicator that uses a Kalman filter to smooth price data and generate actionable long and short signals. This advanced indicator is designed to help traders identify trends, filter out market noise, and optimize their entry and exit points with precision. Let’s explore how this indicator works, its key features, and how it can enhance your trading strategies.
Core Concept: Kalman Filter
The Kalman Filter is a mathematical algorithm used to estimate the state of a system by filtering noisy data. It is widely used in areas such as control systems, signal processing, and time-series analysis. In the context of trading, a Kalman filter can be applied to price data to smooth out short-term fluctuations, providing a clearer view of the underlying trend.
Unlike moving averages, which use fixed weights to smooth data, the Kalman Filter adjusts its estimate dynamically based on the relationship between the process noise and the measurement noise. This makes the filter more adaptive to changing market conditions, providing more accurate trend detection without the lag associated with traditional smoothing techniques.
Please see the original Kalman Price Filter
In this script, the Kalman For Loop applies the Kalman filter to the price source (default set to the closing price) to generate a smoothed price series, which is then used to calculate signals.
Adaptive Smoothing with Process and Measurement Noise
Two key parameters govern the behavior of the Kalman filter:
Process Noise: This controls the extent to which the model allows for uncertainty in price changes. A lower process noise value will make the filter smoother but slower to react to price changes, while a higher value makes it more sensitive to recent price fluctuations.
Measurement Noise: This represents the uncertainty or "noise" in the observed price data. A higher measurement noise value gives the filter more leeway to ignore short-term fluctuations, focusing on the broader trend. Lowering the measurement noise makes the filter more responsive to minor changes in price.
These settings allow traders to fine-tune the Kalman filter’s sensitivity, adjusting it to match their preferred trading style or market conditions.
For-Loop Scoring Mechanism
The Kalman FL further enhances the effectiveness of the Kalman filter by using a for-loop scoring system. This mechanism evaluates the smoothed price over a range of periods (defined by the Calculation Start and Calculation End inputs), assigning a score based on whether the current filtered price is higher or lower than previous values.
Long Signals: A long signal is generated when the for-loop score surpasses the Long Threshold (default set at 20), indicating a strong upward trend. This helps traders identify potential buying opportunities.
Short Signals: A short signal is triggered when the score crosses below the Short Threshold (default set at -10), signaling a potential downtrend or selling opportunity.
These signals are plotted on the chart, giving traders a clear visual indication of when to enter long or short positions.
Customization and Visualization Options
The Kalman For Loop comes with a range of customization options to give traders full control over how the indicator operates and is displayed on the chart:
Kalman Price Source: Choose the price data used for the Kalman filter (default is the closing price), allowing you to apply the filter to other price points like open, high, or low.
Filter Order: Set the order of the Kalman filter (default is 5), controlling how far back the filter looks in its calculations.
Process and Measurement Noise: Fine-tune the sensitivity of the Kalman filter by adjusting these noise parameters.
Signal Line Width and Colors: Customize the appearance of the signal line and the colors used to indicate long and short conditions.
Threshold Lines: Toggle the display of the long and short threshold lines on the chart for better visual clarity.
The indicator also includes the option to color the candlesticks based on the current trend direction, allowing traders to quickly identify changes in market sentiment. In addition, a background color feature further highlights the overall trend by shading the background in green for long signals and red for short signals.
Trading Applications
The Kalman For Loop is a versatile tool that can be adapted to a variety of trading strategies and markets. Some of the primary use cases include:
Trend Following: The adaptive nature of the Kalman filter helps traders identify the start of new trends with greater precision. The for-loop scoring system quantifies the strength of the trend, making it easier to stay in trades for longer when the trend remains strong.
Mean Reversion: For traders looking to capitalize on short-term reversals, the Kalman filter's ability to smooth price data makes it easier to spot when price has deviated too far from its expected path, potentially signaling a reversal.
Noise Reduction: The Kalman filter excels at filtering out short-term price noise, allowing traders to focus on the broader market movements without being distracted by minor fluctuations.
Risk Management: By providing clear long and short signals based on filtered price data, the Kalman FL helps traders manage risk by entering positions only when the trend is well-defined, reducing the chances of false signals.
Alerts and Automation
To further assist traders, the Kalman For Loop includes built-in alert conditions that notify you when a long or short signal is generated. These alerts can be configured to trigger notifications, helping you stay on top of market movements without constantly monitoring the chart.
Final Thoughts
The Kalman For Loop is a powerful and adaptive trading indicator that combines the precision of the Kalman filter with a for-loop scoring mechanism to generate reliable long and short signals. Whether you’re a trend follower or a reversal trader, this indicator offers the flexibility and accuracy needed to navigate complex markets with confidence.
As always, it’s important to backtest the indicator and adjust the settings to fit your trading style and market conditions. No indicator is perfect, and the Kalman FL should be used alongside other tools and sound risk management practices for the best results.
Fourier For Loop [BackQuant]Fourier For Loop
PLEASE Read the following, as understanding an indicator's functionality is essential before integrating it into a trading strategy. Knowing the core logic behind each tool allows for a sound and strategic approach to trading.
Introducing BackQuant's Fourier For Loop (FFL) — a cutting-edge trading indicator that combines Fourier transforms with a for-loop scoring mechanism. This innovative approach leverages mathematical precision to extract trends and reversals in the market, helping traders make informed decisions. Let's break down the components, rationale, and potential use-cases of this indicator.
Understanding Fourier Transform in Trading
The Fourier Transform decomposes price movements into their frequency components, allowing for a detailed analysis of cyclical behavior in the market. By transforming the price data from the time domain into the frequency domain, this indicator identifies underlying patterns that traditional methods may overlook.
In this script, Fourier transforms are applied to the specified calculation source (defaulted to HLC3). The transformation yields magnitude values that can be used to score market movements over a defined range. This scoring process helps uncover long and short signals based on relative strength and trend direction.
Why Use Fourier Transforms?
Fourier Transforms excel in identifying recurring cycles and smoothing noisy data, making them ideal for fast-paced markets where price movements may be erratic. They also provide a unique perspective on market volatility, offering traders additional insights beyond standard indicators.
Calculation Logic: For-Loop Scoring Mechanism
The For Loop Scoring mechanism compares the magnitude of each transformed point in the series, summing the results to generate a score. This score forms the backbone of the signal generation system.
Long Signals: Generated when the score surpasses the defined long threshold (default set at 40). This indicates a strong bullish trend, signaling potential upward momentum.
Short Signals: Triggered when the score crosses under the short threshold (default set at -10). This suggests a bearish trend or potential downside risk.'
Thresholds & Customization
The indicator offers customizable settings to fit various trading styles:
Calculation Periods: Control how many periods the Fourier transform covers.
Long/Short Thresholds: Adjust the sensitivity of the signals to match different timeframes or risk preferences.
Visualization Options: Traders can visualize the thresholds, change the color of bars based on trend direction, and even color the background for enhanced clarity.
Trading Applications
This Fourier For Loop indicator is designed to be versatile across various market conditions and timeframes. Some of its key use-cases include:
Cycle Detection: Fourier transforms help identify recurring patterns or cycles, giving traders a head-start on market direction.
Trend Following: The for-loop scoring system helps confirm the strength of trends, allowing traders to enter positions with greater confidence.
Risk Management: With clearly defined long and short signals, traders can manage their positions effectively, minimizing exposure to false signals.
Final Note
Incorporating this indicator into your trading strategy adds a layer of mathematical precision to traditional technical analysis. Be sure to adjust the calculation start/end points and thresholds to match your specific trading style, and remember that no indicator guarantees success. Always backtest thoroughly and integrate the Fourier For Loop into a balanced trading system.
Thus following all of the key points here are some sample backtests on the 1D Chart
Disclaimer: Backtests are based off past results, and are not indicative of the future .
INDEX:BTCUSD
INDEX:ETHUSD
BINANCE:SOLUSD
Custom Time Range HighlighterCustom Time Range Highlighter
This versatile indicator allows traders to highlight specific time ranges on their charts, accommodating users worldwide by supporting customizable UTC offsets. Traders can define two distinct time ranges, setting start and end hours in their local time zone.
A toggle option enables the display of highlights for today only , ensuring focus on current trading conditions.
Ideal for day traders and those following specific market sessions, this tool enhances visibility of active trading periods and aids in effective trade management.
Deep Crab Harmonic Pattern [TradingFinder] Reversal Zones🔵 Introduction
The Deep Crab pattern is a 5-point extension harmonic structure (X-A-B-C-D) used in technical analysis to identify potential reversal points in financial markets. Like the original Crab pattern, it heavily relies on a 1.618 XA projection to form the Potential Reversal Zone (PRZ).
However, the key difference lies in the B point, which must be an 0.886 retracement of the XA leg. The D point in this pattern typically extends beyond the X point, signaling a strong potential reversal in price movement.
Bullish Deep Crab :
The Bullish Deep Crab is a pattern used in technical analysis to spot potential trend reversals. It signals a shift from a downtrend to an uptrend. Traders enter a buy position at the D point and set a stop-loss below point X, anticipating a price increase.
Bearish Deep Crab :
The Bearish Deep Crab is a reversal pattern that indicates the potential end of an uptrend. Traders enter a sell position at point D and set a stop-loss above point X, expecting the price to fall afterward.
🟣 Crab Vs Deep Crab
The Crab and Deep Crab patterns are both used to identify reversal points in technical analysis, but they differ in terms of correction depth :
Crab : The B point retraces between 38.2% to 61.8% of the XA leg, and point D extends beyond X, indicating a price reversal after a smaller correction.
Deep Crab : The B point retraces more deeply, around 88.6% of the XA leg, and point D has a stronger extension, signaling a reversal after a deeper correction.
The Deep Crab is more suited for identifying stronger price movements.
🔵 How to Use
To effectively use the Deep Crab pattern, it’s essential to correctly identify its five key points (X, A, B, C, and D) based on Fibonacci retracements and extensions. Traders look for a deep retracement at point B, followed by an extended move to point D, which typically signals a strong price reversal.
Once these points are established, traders can strategically enter positions at point D with appropriate stop-loss and take-profit levels, capitalizing on the anticipated market reversal. Proper use of Fibonacci tools is crucial for accurate pattern identification.
🟣 Bullish Deep Crab
To use the Bullish Deep Crab pattern, a trader identifies point D as the key price reversal point in a downtrend. Using Fibonacci tools, points X, A, B, and C are identified, with point B showing an 88.6% retracement of XA, and CD extending 1.618% of XA.
The trader enters a buy position at point D and sets a stop-loss below X, expecting a reversal from a downtrend to an uptrend.
🟣 Bearish Deep Crab
In the Bearish Deep Crab pattern, point D acts as the reversal point in an uptrend. After identifying points X, A, B, and C, D extends 1.618% of XA. Point B retraces 88.6% of XA. Traders enter a sell position at point D and place a stop-loss above X, anticipating a drop in price.
🔵 Setting
🟣 Logical Setting
ZigZag Pivot Period : You can adjust the period so that the harmonic patterns are adjusted according to the pivot period you want. This factor is the most important parameter in pattern recognition.
Show Valid Forma t: If this parameter is on "On" mode, only patterns will be displayed that they have exact format and no noise can be seen in them. If "Off" is, the patterns displayed that maybe are noisy and do not exactly correspond to the original pattern.
Show Formation Last Pivot Confirm : if Turned on, you can see this ability of patterns when their last pivot is formed. If this feature is off, it will see the patterns as soon as they are formed. The advantage of this option being clear is less formation of fielded patterns, and it is accompanied by the latest pattern seeing and a sharp reduction in reward to risk.
Period of Formation Last Pivot : Using this parameter you can determine that the last pivot is based on Pivot period.
🟣 Genaral Setting
Show : Enter "On" to display the template and "Off" to not display the template.
Color : Enter the desired color to draw the pattern in this parameter.
LineWidth : You can enter the number 1 or numbers higher than one to adjust the thickness of the drawing lines. This number must be an integer and increases with increasing thickness.
LabelSize : You can adjust the size of the labels by using the "size.auto", "size.tiny", "size.smal", "size.normal", "size.large" or "size.huge" entries.
🟣 Alert Setting
Alert : On / Off
Message Frequency : This string parameter defines the announcement frequency. Choices include: "All" (activates the alert every time the function is called), "Once Per Bar" (activates the alert only on the first call within the bar), and "Once Per Bar Close" (the alert is activated only by a call at the last script execution of the real-time bar upon closing). The default setting is "Once per Bar".
Show Alert Time by Time Zone : The date, hour, and minute you receive in alert messages can be based on any time zone you choose. For example, if you want New York time, you should enter "UTC-4". This input is set to the time zone "UTC" by default.
🔵 Conclusion
The Deep Crab pattern is a valuable reversal tool in technical analysis, known for its deep retracement and extended price movements.
Unlike other harmonic patterns, it emphasizes identifying critical points where price action is likely to reverse sharply. This pattern works well in both bullish and bearish market scenarios, offering clear signals for entry and exit points.
However, successful application requires a deep understanding of market behavior and precise use of technical tools like Fibonacci retracement. Overall, mastering this pattern can enhance trading strategies and risk management.
Kalman PSaR [BackQuant]Kalman PSaR
Overview and Innovation
The Kalman PSaR combines the well-known Parabolic SAR (PSaR) with the advanced smoothing capabilities of the Kalman Filter . This innovative tool aims to enhance the traditional PSaR by integrating Kalman filtering, which reduces noise and improves trend detection. The Kalman PSaR adapts dynamically to price movements, making it a highly effective indicator for spotting trend shifts while minimizing the impact of false signals caused by market volatility.
Please Find the Basic Kalman Here:
Kalman Filter Dynamics
The Kalman Filter is a powerful algorithm for estimating the true value of a system amidst noisy data. In the Kalman PSaR, this filter is applied to the high, low, and closing prices, resulting in a smoother and more accurate representation of price action. The filter’s parameters—process noise and measurement noise—are customizable, allowing traders to fine-tune the sensitivity of the indicator to market conditions. By reducing the impact of noise, the Kalman-filtered PSaR offers clearer signals for identifying trend reversals and continuations.
Enhanced PSaR Calculation
The traditional Parabolic SAR is a popular trend-following indicator that highlights potential entry and exit points based on price acceleration. In the Kalman PSaR, this calculation is enhanced by the Kalman-filtered prices, providing a smoother and more reliable signal. The indicator continuously updates based on the acceleration factor and max step values, while the Kalman filter ensures that sudden price spikes or market noise do not trigger false signals.
Min Step and Max Step: These settings control the sensitivity of the PSaR. The Min Step sets the initial acceleration factor, while the Max Step limits how fast the PSaR adapts to price changes, helping traders fine-tune the indicator’s responsiveness.
Optional Smoothing Techniques To further enhance the signal clarity, the Kalman PSaR includes an optional smoothing feature. Traders can choose from various smoothing methods, such as SMA, Hull, EMA, WMA, TEMA, and more, to reduce short-term fluctuations and emphasize the underlying trend. The smoothing period is customizable, allowing traders to adjust the indicator’s behavior according to their preferred trading style and timeframe.
Color-Coded Candle Painting The Kalman PSaR features color-coded candles that change according to the trend direction. When the price is above the PSaR, candles are painted green to indicate a long trend, and when the price is below the PSaR, candles are painted red to signal a short trend. This visual representation makes it easy to interpret market sentiment at a glance, improving decision-making speed during fast-moving markets.
Key Features and Customization
Kalman Filter Customization: The process noise and measurement noise parameters allow traders to adjust how aggressively the filter adapts to price changes, making it suitable for both volatile and stable markets.
Smoothing Options: A variety of moving average types, such as SMA, Hull, EMA, and more, can be applied to smooth the PSaR values, ensuring that the signal remains clear even in choppy markets.
Dynamic Trend Detection: The Kalman PSaR dynamically updates based on price movements, helping traders spot trend reversals early while filtering out false signals caused by short-term volatility.
Bar Coloring and PSaR Plotting: Traders can choose to color candles based on trend direction or plot the PSaR directly on the chart for additional visual clarity.
Practical Applications
Trend-Following Strategies: The Kalman PSaR excels in trend-following strategies by providing timely signals of trend changes. The dynamic nature of the indicator allows traders to capture significant price movements while avoiding market noise.
Reversal Identification: The indicator’s ability to filter out noise and provide smoother signals makes it ideal for identifying reversals in volatile markets.
Risk Management: By plotting clear stop levels based on the PSaR, traders can use this indicator to effectively manage risk, placing stop-loss orders at key points based on the trend direction.
Conclusion
The Kalman PSaR is a fusion of the classic Parabolic SAR and the Kalman filter, offering enhanced trend detection with reduced noise. Its customizable filtering and smoothing options, combined with dynamic trend-following capabilities, make it a versatile tool for traders seeking to improve their timing and signal accuracy. The adaptive nature of the Kalman filter, combined with the robust PSaR logic, helps traders stay on the right side of the market and manage risk more effectively.
Fisher Divergence Overlay [BackQuant]Fisher Divergence Overlay
You can find the other Fisher Script Here !
Overlay Adaptation The Fisher Divergence Overlay is a newly enhanced version of the original Fisher Transformation indicator, designed specifically to be plotted directly on price charts. This adaptation allows traders to visualize Fisher Transform signals, divergences, and trend shifts directly over the price action, offering a more intuitive way to monitor market trends and potential reversals without the need for separate indicator windows. The overlay structure is particularly useful for spotting divergences and shifts in momentum as they relate to key price levels.
Why Turn the Fisher into an Overlay?
By transforming the Fisher Divergence indicator into an overlay, traders gain a more direct view of the relationship between price movements and the Fisher Transformation's signals. Divergences and midline crossovers, key components of the Fisher strategy, can now be clearly seen relative to the current price action. The decision to integrate this functionality as an overlay allows for a cleaner and more insightful trading experience, helping traders make quicker, more informed decisions based on market dynamics.
Midline Cross Signals : The overlay makes it easy to see when the Fisher Transform crosses above or below the midline, a critical signal for potential trend reversals.
Divergence Signals : Both regular and hidden divergences are plotted directly over price bars, offering immediate visual confirmation of potential trend shifts.
Key Features of the Overlay Version
Kaufman Adaptive Moving Average (KAMA): The Fisher Transformation in this overlay version can be adapted using Kaufman’s Adaptive Moving Average (KAMA). This enhances the Fisher's responsiveness to current market volatility, smoothing out price data while maintaining the accuracy of trend signals.
Divergence Detection: The overlay includes both regular and hidden bullish and bearish divergence detection, with these divergences plotted directly on the price chart. This visual feedback makes it easier for traders to spot when the momentum of the Fisher Transform deviates from the actual price movement, often signaling potential reversals.
Dynamic Bar Coloring: The bars are color-coded based on either the Fisher trend or divergences, allowing traders to visually interpret market sentiment without additional analysis. Green bars signal an upward trend or bullish divergence, while red bars indicate a downward trend or bearish divergence.
Take Profit Hues: In conjunction with a normalized RSI, the overlay includes background hues for overbought and oversold conditions, providing additional context for exit points or potential reversals.
How to Use the Fisher Overlay Traders can use this overlay to streamline their workflow by having both the Fisher signals and price action in the same visual space. The key signals include:
Midline Cross Signals: A crossover of the Fisher Transform above the midline often indicates a shift toward bullish momentum, while a cross below suggests bearish momentum.
Divergences: Regular and hidden divergences, displayed directly on the chart, help traders identify moments when the momentum of the Fisher Transform is in contrast with price movements, signaling potential reversals.
RSI Confluence: Overbought and oversold signals, provided by the integrated RSI, give further insight into potential exhaustion points in the market, marked by background color changes on the chart.
Strategic Value of the Fisher Divergence Overlay
This overlay offers a streamlined, efficient way to interpret Fisher Transform signals, divergences, and confluence signals like RSI in real-time. The visual integration of these signals with price action enhances decision-making by providing immediate context, making it easier to spot high-probability trade setups.
Trend Confirmation: The overlay version helps confirm trends by visually aligning Fisher Transform signals with price levels. Traders can use this feature to strengthen their conviction before entering or exiting a trade.
Adaptability: With the option to use KAMA for adaptive price smoothing, this overlay remains responsive across different market environments, making it suitable for both trending and volatile markets.
Summary and Interpretation Tips
It enhances the traditional Fisher Transform with visual elements like divergence detection, RSI confluence, and midline cross signals. By overlaying these elements directly on the price chart, traders can quickly interpret key signals and make better trading decisions.
Use this indicator to identify trend shifts and potential reversals by focusing on midline crossovers and divergences. The visual cues—bar colors, divergence labels, and background hues—make it easy to spot actionable moments without cluttering the chart. For best results, combine this overlay with other trend-following tools to confirm your trades and maximize the utility of Fisher Transform signals.
Multi-Kernel CCI [BackQuant]Multi-Kernel CCI
Conceptual Foundation and Innovation
It offers a fresh take on the Commodity Channel Index (CCI) by integrating three distinct kernel functions—Exponential Decay, Gaussian Decay, and Cosine Decay—to create a more robust and adaptive momentum indicator. The use of these kernel functions allows the CCI calculation to be more responsive to price changes while smoothing out noise, providing traders with clearer trend signals and reducing false alerts in varying market conditions.
Technical Composition and Calculation
The core of this indicator is a multi-kernel approach to calculating the CCI, where three different decay kernels are applied to the price source. Each kernel provides a unique weighting mechanism for price data over a user-defined lookback period. The result is an average of these three kernel calculations, which serves as the foundation for the CCI calculation. This innovative approach makes the Multi-Kernel CCI more adaptive to different market conditions compared to traditional CCI calculations.
Exponential Decay Kernel: Applies an exponential weighting to recent price data, giving more importance to recent values while smoothing out older data.
Gaussian Decay Kernel: Weights data using a Gaussian function, ensuring smooth transitions between price points and reducing outliers' impact.
Cosine Decay Kernel: Utilizes a cosine function to apply a unique oscillating weight to the data, capturing cyclical market movements more effectively.
Adaptive Thresholding: Like the Adaptive Momentum Oscillator, this indicator adjusts its long and short thresholds dynamically using percentile-based calculations over historical CCI values.
Features and User Inputs The Multi-Kernel CCI offers a wide range of customization options for traders:
Kernel Calculation Length & Alpha: Traders can fine-tune the sensitivity of the CCI by adjusting the length of the kernel calculation and the alpha parameter for the Exponential Decay Kernel.
Adaptive Thresholds: The indicator provides percentile-based thresholds for both long and short signals, allowing traders to dynamically adjust their signals based on historical data.
Extreme Value Detection: This feature highlights extreme overbought and oversold conditions with customizable thresholds and background hues, visually aiding in identifying high-probability reversal zones.
Divergence Detection: The script includes a divergence detection feature, identifying regular and hidden bullish or bearish divergences to help traders spot potential trend reversals.
Practical Applications The Multi-Kernel CCI excels in markets where adaptive trend detection and momentum confirmation are critical. Traders can leverage this tool in several ways:
Adaptive Trend Following: The dynamically adjusting thresholds allow traders to capture trends more effectively while avoiding false signals during consolidations or choppy markets.
Reversal Detection: The multi-kernel approach ensures that reversals are detected with greater precision, particularly in volatile markets where traditional indicators might fail.
Divergence Identification: With built-in divergence detection, the indicator provides traders with an early warning of potential trend reversals, helping to time their entries and exits more effectively.
Advantages and Strategic Value The Multi-Kernel CCI offers several strategic advantages over traditional CCI indicators:
Multi-Kernel Smoothing:
By using multiple decay kernels, this CCI calculation is better suited to detect subtle changes in market momentum, reducing the impact of noise and providing clearer trend signals.
Dynamic Thresholds:
The adaptive percentile-based thresholds ensure that the indicator remains relevant across different market conditions, enhancing signal accuracy.
Visual and Analytical Aids:
With features like extreme value detection and divergence spotting, this indicator equips traders with powerful tools to confirm trend strength and identify potential reversals.
Summary and Usage Tips
The Multi-Kernel CCI is a highly versatile tool for traders seeking a more adaptive and robust momentum indicator. Its multi-kernel foundation provides smoother, more reliable signals, while the adaptive thresholds and divergence detection features help traders refine their entries and exits. The dynamic nature of this indicator makes it ideal for both trend-following and reversal strategies in volatile markets.
Traders should experiment with the kernel calculation length and alpha parameter to align the indicator's sensitivity with their specific trading style and market conditions. Additionally, the adaptive thresholds can be fine-tuned to ensure the CCI captures the most significant trend changes without being overly reactive to short-term fluctuations.
Thus following all of the key points here are some sample backtests on the 1D Chart
Disclaimer: Backtests are based off past results, and are not indicative of the future.
INDEX:BTCUSD
INDEX:ETHUSD
BINANCE:SOLUSD
Kalman Filter RoC with Adaptive Thresholds [BackQuant]Kalman Filter RoC with Adaptive Thresholds
Another Kalman Script !!
Please Find the Basic Kalman Here:
Overview and Purpose
The Kalman Filter RoC with Adaptive Thresholds is an advanced tool designed for traders seeking to refine their trend detection and momentum analysis. By combining the robustness of the Kalman filter with the Rate of Change (RoC) indicator, this tool offers a highly responsive and adaptive method to identify shifts in market trends. The inclusion of adaptive thresholding further enhances the indicator’s precision by dynamically adjusting to market volatility, providing traders with reliable entry and exit signals.
Kalman Filter Dynamics
The Kalman Filter is renowned for its ability to estimate the true state of a system amidst noisy data. In this indicator, the Kalman filter is applied to the price data to smooth out fluctuations and generate a more accurate representation of the underlying trend. This is particularly useful in volatile markets where noise can obscure the true direction of price movements. The Kalman filter adapts in real-time based on user-defined parameters, such as process noise and measurement noise, making it highly customizable for different market conditions.
Rate of Change (RoC) and Smoothing The Rate of Change (RoC) is a classic momentum indicator that measures the percentage change in price over a specific period. By integrating it with the Kalman-filtered price, the RoC becomes more responsive to genuine price trends while filtering out short-term noise. An optional smoothing feature using the ALMA (Arnaud Legoux Moving Average) further refines the signal, allowing traders to adjust the calculation length and smoothing factor (sigma) for even greater precision.
Adaptive Thresholds A key innovation in this indicator is the adaptive thresholding mechanism. Traditional RoC indicators rely on static thresholds to identify overbought or oversold conditions, but the Kalman Filter RoC adapts these thresholds dynamically. The adaptive thresholds are calculated based on the historical volatility of the filtered RoC values, allowing the indicator to adjust in response to changing market conditions. This feature reduces the risk of false signals in choppy or highly volatile markets.
Divergence Detection The Kalman Filter RoC also includes divergence detection, helping traders identify when the momentum of the RoC diverges from the price action. Divergences can often signal potential reversals or trend continuations, making them a valuable tool in any trader’s toolkit. Regular and hidden divergences are plotted directly on the chart, providing visual cues for traders to act upon.
Customization and Flexibility This indicator offers a wide range of customization options, making it suitable for various trading strategies and market conditions:
Process Noise & Measurement Noise: These parameters control how sensitive the Kalman filter is to price changes and help traders fine-tune the balance between noise reduction and signal responsiveness.
ALMA Smoothing: Traders can apply ALMA smoothing to the RoC signal to reduce short-term volatility and improve signal clarity.
Adaptive Threshold Calculation Period: The length of the lookback period for the adaptive thresholds can be adjusted, allowing traders to tailor the indicator to fit their specific trading style.
Practical Applications
Trend Detection: The Kalman-filtered RoC helps identify shifts in momentum, making it easier for traders to spot emerging trends early. The dynamic thresholding ensures that these signals are reliable, even in volatile markets.
Divergence Trading: Divergences between the RoC and price action are clear indicators of potential trend reversals. The visual plotting of divergences simplifies the process of identifying these opportunities.
Momentum Analysis: The combination of Kalman filtering and RoC provides a smoother, more accurate view of market momentum, helping traders stay on the right side of the market.
Conclusion
The Kalman Filter RoC is a powerful and adaptable tool that merges advanced filtering techniques with momentum analysis. Its real-time responsiveness and dynamic thresholding make it a highly effective indicator for identifying trends, managing risk, and capitalizing on divergence signals. Traders looking to enhance their trend-following or momentum strategies will find this indicator to be a valuable addition to their toolkit.
Thus following all of the key points here are some sample backtests on the 1D Chart
Disclaimer: Backtests are based off past results, and are not indicative of the future.
INDEX:BTCUSD
INDEX:ETHUSD
BINANCE:SOLUSD
Adaptive Momentum Oscillator [BackQuant]Adaptive Momentum Oscillator
Please take time to read the following.
Conceptual Foundation and Innovation
The Adaptive Momentum Oscillator brings a new approach to momentum trading by introducing percentile-based adaptive thresholding. Unlike traditional momentum oscillators that rely on static overbought and oversold levels, this indicator adjusts dynamically to changing market conditions, providing more relevant signals in real-time. By combining percentile-based thresholds with a smoothed momentum oscillator, this tool allows traders to detect trend shifts with a higher degree of accuracy.
Technical Composition and Calculation
The core of this oscillator uses a lookback period to calculate the highest and lowest values of a smoothed price source (using a non-robust moving average). These values are then used to compute the oscillator, which normalizes the current price between the lookback high and low. The true innovation lies in its adaptive thresholds, which adjust based on percentiles of past oscillator values over a user-defined lookback period.
Lookback Period: The indicator checks the highest and lowest smoothed price over a set period, which becomes the basis for calculating momentum.
Percentile-Based Thresholds: The upper and lower thresholds are dynamically set at user-defined percentiles of historical momentum values, allowing the oscillator to adapt to the volatility and strength of the market.
Smoothing Length: Users can adjust the smoothing of the source input to fine-tune the sensitivity of the oscillator.
Features and User Inputs offer a host of customizable settings to suit different market conditions and trading strategies:
Adaptive Thresholding: Traders can set the lookback period and define the percentile levels for the upper (long) and lower (short) thresholds. This provides the ability to dynamically adjust to changing market conditions and avoid static thresholds that may become irrelevant over time.
Signal Line Customization: Users can configure the signal line width, colors for long, short, and neutral conditions, and choose whether to display adaptive threshold lines on the chart.
Candle Coloring: An optional feature allows traders to color the price bars based on the oscillator's trend signal, adding a visual confirmation layer for trend shifts.
Practical Applications
This oscillator is particularly effective in markets where the strength and direction of momentum are essential for identifying potential trend reversals or confirming ongoing trends. Traders can leverage the Adaptive Momentum Oscillator to:
Capture Adaptive Trends: The percentile-based thresholds adjust dynamically, ensuring that traders catch significant trends while filtering out market noise.
Avoid False Signals: By adapting to historical momentum levels, the oscillator reduces the risk of false breakouts or breakdowns, allowing for more reliable entries and exits.
Optimize Entries and Exits: With dynamically adjusting thresholds, the oscillator helps traders time their positions more effectively, minimizing the risk of getting caught in choppy or uncertain markets.
Advantages and Strategic Value
It offers a clear advantage over traditional static oscillators by continuously adjusting its sensitivity to market conditions. The adaptive percentile thresholds ensure that the indicator remains relevant, regardless of changes in volatility or market direction. This feature, combined with a customizable UI, makes the Adaptive Momentum Oscillator a powerful tool for traders looking to refine their momentum-based strategies with dynamic thresholds.
Summary and Usage Tips
The Adaptive Momentum Oscillator is a versatile tool for both trend-following and contrarian traders. Its dynamic nature allows for better alignment with current market conditions, while its user-friendly inputs offer extensive customization options. Traders are encouraged to experiment with the percentile-based threshold settings to find the optimal balance between signal sensitivity and noise reduction, particularly in fast-moving or volatile markets.
This indicator is best used in combination with other trend-confirmation tools, offering a dynamic layer to your trading system.
Thus following all of the key points here are some sample backtests on the 1D Chart
Disclaimer: Backtests are based off past results, and are not indicative of the future.
INDEX:BTCUSD
INDEX:ETHUSD
BINANCE:SOLUSD
Bat Harmonic Pattern [TradingFinder] Bat Chart Indicator🔵 Introduction
The Bat Harmonic Pattern, created by Scott Carney in the 1990s, is a sophisticated tool in technical analysis, used to identify potential reversal points in price movements by leveraging Fibonacci ratios.
This pattern is classified into two primary types: the Bullish Bat Pattern, which signals the end of a downtrend and the beginning of an uptrend, and the Bearish Bat Pattern, which indicates the conclusion of an uptrend and the onset of a downtrend.
🟣 Bullish Bat Pattern
The Bullish Bat Pattern is designed to identify when a downtrend is likely to end and a new uptrend is about to begin. The key feature of this pattern is Point D, which typically aligns near the 88.6% Fibonacci retracement of the XA leg.
This point is considered a strong buy zone. When the price reaches Point D after a significant downtrend, it often indicates a potential reversal, presenting a buying opportunity for traders anticipating the start of an upward movement.
🟣 Bearish Bat Pattern
In contrast, the Bearish Bat Pattern forms when an uptrend is nearing its conclusion. Point D, which also typically aligns near the 88.6% Fibonacci retracement of the XA leg, serves as a critical point for traders.
This point is regarded as a strong sell zone, signaling that the uptrend may be ending, and a downtrend could be imminent. Traders often open short positions when they identify this pattern, aiming to capitalize on the anticipated downward movement.
🔵 How to Use
The Bat Pattern consists of five key points: X, A, B, C, and D, and four waves: XA, AB, BC, and CD. Fibonacci ratios play a crucial role in this pattern, helping traders pinpoint precise entry and exit points. In both the Bullish and Bearish Bat Patterns, the 88.6% retracement of the XA leg is a critical level for identifying potential reversal points.
🟣 Bullish Bat Pattern
Traders typically enter buy positions after Point D forms, expecting the downtrend to end and a new uptrend to start. This point, located near the 88.6% retracement of the XA leg, serves as a reliable buy signal.
🟣 Bearish Bat Pattern
Traders usually open short positions after identifying Point D, expecting the uptrend to end and a downtrend to begin. This point, also near the 88.6% retracement of the XA leg, acts as a valid sell signal.
🟣 Trading Tips for the Bat Pattern
Accurate Fibonacci Point Identification : Accurately identify Points X, A, B, C, and D, and calculate the Fibonacci ratios between these points. Point D should ideally be near the 88.6% retracement of the XA leg.
Signal Confirmation with Other Tools : To enhance the pattern's accuracy, avoid trading solely based on the Bat Pattern.
Risk Management : Always use stop-loss orders. In a Bullish Bat Pattern, place the stop-loss below Point X, and in a Bearish Bat Pattern, above Point X. This helps limit potential losses if the pattern fails.
Wait for Price Movement Confirmation : After identifying Point D, wait for the price to move in the anticipated direction to confirm the pattern's validity before entering a trade.
Set Realistic Profit Targets : Use Fibonacci retracement levels to set realistic profit targets, such as 38.2%, 50%, and 61.8% retracement levels of the CD leg. This strategy helps maximize profits and prevents premature exits.
🔵 Setting
🟣 Logical Setting
ZigZag Pivot Period : You can adjust the period so that the harmonic patterns are adjusted according to the pivot period you want. This factor is the most important parameter in pattern recognition.
Show Valid Forma t: If this parameter is on "On" mode, only patterns will be displayed that they have exact format and no noise can be seen in them. If "Off" is, the patterns displayed that maybe are noisy and do not exactly correspond to the original pattern.
Show Formation Last Pivot Confirm : if Turned on, you can see this ability of patterns when their last pivot is formed. If this feature is off, it will see the patterns as soon as they are formed. The advantage of this option being clear is less formation of fielded patterns, and it is accompanied by the latest pattern seeing and a sharp reduction in reward to risk.
Period of Formation Last Pivot : Using this parameter you can determine that the last pivot is based on Pivot period.
🟣 Genaral Setting
Show : Enter "On" to display the template and "Off" to not display the template.
Color : Enter the desired color to draw the pattern in this parameter.
LineWidth : You can enter the number 1 or numbers higher than one to adjust the thickness of the drawing lines. This number must be an integer and increases with increasing thickness.
LabelSize : You can adjust the size of the labels by using the "size.auto", "size.tiny", "size.smal", "size.normal", "size.large" or "size.huge" entries.
🟣 Alert Setting
Alert : On / Off
Message Frequency : This string parameter defines the announcement frequency. Choices include: "All" (activates the alert every time the function is called), "Once Per Bar" (activates the alert only on the first call within the bar), and "Once Per Bar Close" (the alert is activated only by a call at the last script execution of the real-time bar upon closing). The default setting is "Once per Bar".
Show Alert Time by Time Zone : The date, hour, and minute you receive in alert messages can be based on any time zone you choose. For example, if you want New York time, you should enter "UTC-4". This input is set to the time zone "UTC" by default.
🔵 Conclusion
The Bat Harmonic Pattern is a powerful tool in technical analysis, offering traders the ability to identify critical reversal points using Fibonacci ratios. By recognizing the Bullish and Bearish Bat Patterns, traders can anticipate potential trend reversals and make informed trading decisions.
However, it is essential to combine the Bat Pattern with other technical analysis tools and confirm signals for better trading outcomes. With proper use, this pattern can help traders minimize risk and optimize their entry and exit points in the market.
Volatility with Power VariationVolatility Analysis using Power Variation
The "Volatility with Power Variation" indicator is designed to measure market volatility. It focuses on providing traders with a clear understanding of how much the market is moving and how this movement changes over time.. This indicator helps in identifying potential periods of market expansion or contraction, based on volatility.
What the indicator does:
This indicator analyzes volatility which refers to the degree of variation in the returns of a financial instrument over time. It's an important measure to understand how much the price and returns of a asset fluctuates. High volatility means large price swings, meanwhile low volatility indicates smaller and consolidating movements. Realized (Historical) Volatility refers to volatility based on past price data.
Power Variation
Power Variation is an extension of the traditional methods used to calculate realized volatility. Instead of simply summing up squared returns (as done in calculating variance), Power Variation raises the magnitude of returns to a power p . This allows the indicator to capture different types of market behavior depending on the chosen value of p .
When P = 2, the Power variation behaves like a traditional variance measure. Lower values of p (e.g., p=1) make the indicator more sensitive to smaller price changes, meanwhile higher values make it more responsive to large jumps, but smaller price moves wont affect the measure that much or won't most likely.
Bipower Variation
Bipower variation is another method used to analyze the changes in price. It specifically isolates the continuous part of price movements from the jumps, which can help by understanding whether volatility is coming from regular market activity or from sharp, sudden moves.
How to Use the Indicator.
Understand Realized and Historical Volatility. Volatility after periods of low volatility you can eventually expect a expansion or an increase in volatility. Conversely, after periods of high volatility, the market often contracts and volatility decreases. If the variation plot is really low and you start seeing it increasing, shown by the standard deviation channels and moving average and you see it trending and increasing then that means you can expect for volatility to increase which means more price moves and expansions. Also if the scaling seems messed up, then use the logarithmic chart scale.
DEMA Adaptive DMI [BackQuant]DEMA Adaptive DMI
PLEASE Read the following, knowing what an indicator does at its core before adding it into a system is pivotal. The core concepts can allow you to include it in a logical and sound manner.
Conceptual Foundation and Innovation
The DEMA Adaptive DMI blends the Double Exponential Moving Average (DEMA) with the Directional Movement Index (DMI) to offer a unique approach to trend-following. By applying DEMA to the high and low prices, this indicator refines the traditional DMI calculation, enhancing its responsiveness to price changes. This results in a more adaptive and timely measure of market trends and momentum, providing traders with a more refined tool for capturing directional movements in the market.
Technical Composition and Calculation
At its core, the DEMA Adaptive DMI calculates the DEMA for both the high and low prices over a user-defined period. This dual application of DEMA serves to smooth out price fluctuations while retaining sensitivity to market movements. The DMI is then derived from the changes in these DEMA values, producing a set of plus and minus directional indicators that reflect the prevailing trend. Additionally, an Average Directional Index (ADX) is computed to measure the strength of the trend, with the entire process being dynamically adjusted based on the DEMA calculations.
DEMA Application:
The DEMA is applied to both high and low prices to reduce lag and provide a smoother representation of price action.
Directional Movement Calculation: The DMI is calculated using the smoothed price changes, resulting in plus and minus indicators that accurately reflect market trends.
ADX Calculation:
The ADX is computed to quantify the strength of the trend, offering traders insight into whether the market is trending strongly or is in a phase of consolidation.
Features and User Inputs The DEMA Adaptive DMI offers a range of customizable options to suit different trading styles and market conditions:
DEMA Calculation Period: Users can set the period for the DEMA calculation, allowing for adjustments based on the desired sensitivity.
DMI Length: The length of the DMI calculation can be adjusted, providing flexibility in how trends are measured.
ADX Smoothing Period: The smoothing period for the ADX can be customized to fine-tune the trend strength measurement.
Divergence Detection: Optional divergence detection features allow traders to spot potential reversals based on the DMI and price action.
Visualization options include static high and low levels to mark extreme DMI thresholds, the ability to color bars according to trend direction, and background hues to highlight overbought and oversold conditions.
Practical Applications
The DEMA Adaptive DMI is particularly effective in markets where trend strength and direction are crucial for successful trading. Traders can leverage this indicator to:
Identify Trend Reversals:
Detect potential trend reversals by monitoring the DMI and ADX in conjunction with divergence signals.
Trend Confirmation:
Use the DEMA-based DMI to confirm the strength and direction of a trend, aiding in the timing of entries and exits.
Strategic Positioning:
The indicator's responsiveness allows traders to position themselves effectively in fast-moving markets, reducing the risk of late entries or exits.
Advantages and Strategic Value
By integrating the DEMA with the DMI, this indicator provides a more adaptive and timely measure of market trends. The reduced lag from the DEMA ensures that traders receive signals that are closely aligned with current market conditions, while the dynamic DMI calculation offers a more accurate representation of trend direction and strength. This makes the DEMA Adaptive DMI a valuable tool for traders looking to enhance their trend-following strategies with a focus on precision and adaptability.
Summary and Usage Tips
The DEMA Adaptive DMI is a sophisticated trend-following indicator that combines the benefits of DEMA and DMI into a single, powerful tool. Traders are encouraged to incorporate this indicator into their trading systems for a more nuanced and responsive approach to trend detection and confirmation. Whether used for identifying trend reversals, confirming trend strength, or strategically positioning in the market, the DEMA Adaptive DMI offers a versatile and reliable solution for trend-following strategies.
Thus following all of the key points here are some sample backtests on the 1D Chart
Disclaimer: Backtests are based off past results, and are not indicative of the future.
INDEX:BTCUSD
INDEX:ETHUSD
BINANCE:SOLUSD
