Volume Flow RatioVolume Flow Ratio (VFR) Indicator
Overview
The Volume Flow Ratio (VFR) is a sophisticated volume analysis tool that measures current trading volume relative to the maximum volume of the previous period. Unlike traditional volume indicators that show raw volume or simple moving averages, VFR provides context by comparing current activity to recent maximum activity levels.
Core Features
1. Split Period Analysis
- Multiple Timeframe Options:
- Daily: Compares to previous day's maximum
- Weekly: Week-to-week comparison
- NYSE Weekly: Specialized for stock market trading (Monday-Friday only)
- Monthly: Month-to-month analysis
- Quarterly: Quarter-to-quarter perspective
- Yearly: Year-over-year volume comparison
2. Ratio-Based Measurement
- Displays volume as a ratio (0 to 1+) rather than raw numbers
- 1.0 represents volume equal to previous period's maximum
- Example: If previous max was 50,000 contracts:
- Current volume of 25,000 shows as 0.5
- Current volume of 75,000 shows as 1.5
3. Triple Coloring Modes
- Moving Average Based:
- Compares current ratio to its moving average
- Customizable MA period
- Green: Above MA (higher than average activity)
- Red: Below MA (lower than average activity)
- Previous Candle Comparison:
- Simple increase/decrease from previous bar
- Green: Higher than previous bar
- Red: Lower than previous bar
- Candle Color Based:
- Syncs with price action
- Green: Bullish candles (close > open)
- Red: Bearish candles (close < open)
Primary Use Cases
1. Volume Profile Analysis
- Perfect for traders who need to understand when markets are most active
- Helps identify unusual volume spikes relative to recent history
- Useful for timing entries and exits based on market participation
2. Market Activity Traders
Ideal for traders who:
- Need to identify high-liquidity periods
- Want to avoid low-volume periods
- Look for volume breakouts or divergences
- Trade based on institutional participation levels
3. Mean Reversion Traders
Helps identify:
- Overextended volume conditions (potential reversals)
- Volume exhaustion points
- Return to normal volume levels after spikes
4. Momentum Traders
Useful for:
- Confirming trend strength through volume
- Identifying potential trend exhaustion
- Validating breakouts with volume confirmation
Advantages Over Traditional Volume Indicators
1. Contextual Analysis
- Shows relative strength rather than raw numbers
- Easier to compare across different time periods
- Automatically adjusts to changing market conditions
2. Period-Specific Insights
- Respects natural market cycles (daily, weekly, monthly)
- Special handling for NYSE trading days
- Eliminates weekend noise in stock market analysis
3. Flexible Visualization
- Three distinct coloring methods for different trading styles
- Clear reference line at 1.0 for quick analysis
- Histogram style for easy pattern recognition
Best Practices
For Day Traders
- Use Daily split for intraday volume patterns
- MA coloring mode with shorter periods (5-10)
- Focus on ratios during market hours
For Swing Traders
- Weekly or NYSE Weekly splits
- Longer MA periods (15-20)
- Look for sustained volume patterns
For Position Traders
- Monthly or Quarterly splits
- Candle color mode for trend confirmation
- Focus on major volume shifts
Limitations
- Requires one full period to establish baseline
- May be less effective in extremely low volume conditions
- NYSE Weekly mode specific to stock market hours
This indicator is particularly valuable for traders who understand that volume is a crucial component of price action but need a more sophisticated way to analyze it than simple volume bars. It's especially useful for those who trade based on market participation levels and need to quickly identify whether current volume is significant relative to recent history.
Recherche dans les scripts pour "Pattern recognition"
Opening Range BoxIndicator Name: Opening Range Box with Extensions
Author: YanivBull
Description:
The Opening Range Box with Extensions is a powerful tool designed to visualize the trading range established during the first 30 minutes of a market session, a critical period for setting the day's trend. This indicator plots a box representing the high and low prices formed within this opening range, with dashed extension lines projecting these levels forward throughout the session.
Its primary purpose is to identify the boundaries of the initial trend at the start of trading. When these boundaries are breached, it serves as a trigger for potential trading opportunities: a breakout above the box high signals a possible long entry, while a breakdown below the box low indicates a potential short entry. The indicator also includes historical boxes for up to 5 previous days (configurable), allowing traders to analyze past opening ranges and their extensions for context and pattern recognition.
Key Features:
Customizable session start time (hour and minute) to adapt to various markets (e.g., NYSE, DAX, etc.).
Displays the current session's opening range box in blue and historical boxes in gray.
Plots dashed extension lines from the high and low of each box, limited to 500 bars or the end of the trading day.
Adjustable number of historical days (1-20, default 5).
Usage:
Set the Session Start Hour and Session Start Minute according to your market's opening time (relative to your chart's timezone, e.g., UTC+2). Watch for price action around the box boundaries—breakouts above the high or below the low can be used as signals for initiating long or short trades, respectively. Combine with other technical analysis tools for confirmation.
This indicator is ideal for day traders looking to capitalize on early session momentum and breakout strategies.
EMA Study Script for Price Action Traders, v2JR_EMA Research Tool Documentation
Version 2 Enhancements
Version 2 of the JR_EMA Research Tool introduces several powerful features that make it particularly valuable for studying price action around Exponential Moving Averages (EMAs). The key improvements focus on tracking and analyzing price-EMA interactions:
1. Cross Detection and Counting
- Implements flags for crossing bars that instantly identify when price crosses above or below the EMA
- Maintains running counts of closes above and below the EMA
- This feature helps students understand the persistence of trends and the frequency of EMA interactions
2. Bar Number Tracking
- Records the specific bar number when EMA crosses occur
- Stores the previous crossing bar number for reference
- Enables precise measurement of time between crosses, helping identify typical trend durations
3. Variable Reset Management
- Implements sophisticated reset logic for all counting variables
- Ensures accuracy when analyzing multiple trading sessions
- Critical for maintaining clean data when studying patterns across different timeframes
4. Cross Direction Tracking
- Monitors the direction of the last EMA cross
- Helps students identify the current trend context
- Essential for understanding trend continuation vs reversal scenarios
Educational Applications
Price-EMA Relationship Studies
The tool provides multiple ways to study how price interacts with EMAs:
1. Visual Analysis
- Customizable EMA bands show typical price deviation ranges
- Color-coded fills help identify "normal" vs "extreme" price movements
- Three different band calculation methods offer varying perspectives on price volatility
2. Quantitative Analysis
- Real-time tracking of closes above/below EMA
- Running totals help identify persistent trends
- Cross counting helps understand typical trend duration
Research Configurations
EMA Configuration
- Adjustable EMA period for studying different trend timeframes
- Customizable EMA color for visual clarity
- Ideal for comparing different EMA periods' effectiveness
Bands Configuration
Three distinct calculation methods:
1. Full Average Bar Range (ABR)
- Uses the entire range of price movement
- Best for studying overall volatility
2. Body Average Bar Range
- Focuses on the body of the candle
- Excellent for studying conviction in price moves
3. Standard Deviation
- Traditional statistical approach
- Useful for comparing to other technical studies
Signal Configuration
- Optional signal plotting for entry/exit studies
- Helps identify potential trading opportunities
- Useful for backtesting strategy ideas
Using the Tool for Study
Basic Analysis Steps
1. Start with the default 20-period EMA
2. Observe how price interacts with the EMA line
3. Monitor the data window for quantitative insights
4. Use band settings to understand normal price behavior
Advanced Analysis
1. Pattern Recognition
- Use the cross counting system to identify typical pattern lengths
- Study the relationship between cross frequency and trend strength
- Compare different timeframes for fractal analysis
2. Volatility Studies
- Compare different band calculation methods
- Identify market regimes through band width changes
- Study the relationship between volatility and trend persistence
3. Trend Analysis
- Use the closing price count system to measure trend strength
- Study the relationship between trend duration and subsequent reversals
- Compare different EMA periods for optimal trend following
Best Practices for Research
1. Systematic Approach
- Start with longer timeframes and work down
- Document observations about price behavior in different market conditions
- Compare results across multiple symbols and timeframes
2. Data Collection
- Use the data window to record significant events
- Track the number of bars between crosses
- Note market conditions when signals appear
3. Optimization Studies
- Test different EMA periods for your market
- Compare band calculation methods for your trading style
- Document which settings work best in different market conditions
Technical Implementation Notes
This tool is particularly valuable for educational purposes because it combines visual and quantitative analysis in a single interface, allowing students to develop both intuitive and analytical understanding of price-EMA relationships.
Dual Zigzag [Trendoscope®]🎲 Dual Zigzag indicator is built on recursive zigzag algorithm. It is very similar to other zigzag indicators published by us and other authors. However, the key point here is, the indicator draws zigzag on both price and any other plot based indicator on separate layouts.
Before we get into the indicator, here are some brief descriptions of the underlying concepts and key terminologies
🎯 Zigzag
Zigzag indicator breaks down price or any input series into a series of Pivot Highs and Pivot Lows alternating between each other. Zigzags though shows pivot high and lows, should not be used for buying at low and selling at high. The main application of zigzag indicator is for the visualisation of market structure and this can be used as basic building block for any pattern recognition algorithms.
🎯 Recursive Zigzag Algorithm
Recursive zigzag algorithm builds zigzag on multiple levels and each level of zigzag is based on the previous level pivots. The level zero zigzag is built on price. However, for level 1, instead of price level 0 zigzag pivots are used. Similarly for level 2, level 1 zigzag pivots are used as base.
🎲 Components Dual Zigzag Indicator
Here are the components of Dual zigzag indicator
Built in Oscillator - Indicator has built in oscillator options for plotting RSI (Relative Strength Index), MFI (Money Flow Index), cci (Commodity Channel Index) , CMO (Chande Momentum Oscillator), COG (Center of Gravity), and ROC (Rate of Change). Apart from the given built in oscillators, users can also use a custom external output as base. The oscillators are not printed on the price pane. But, printed on a separate indicator overlay.
Zigzag On Oscillator - Recursive zigzag is calculated and printed on the oscillator series. Each pivot high and pivot low also prints a label having the retracement ratios, and price levels at those points. Zigzag on the oscillator is also printed on the indicator overlay pane.
Zigzag on Price - Recursive zigzag calculated based on price and printed on the price pane. This is made possible by using force_overlay option present in the drawing objects. At each zigzag pivot levels, the label having price retracement ratios, and oscillator values are printed.
It is called dual zigzag because, the indicator calculates the zigzag on both price and oscillator series of values and prints them separately on different panes on the chart.
🎲 Indicator Settings
Settings include
Theme display settings to get the right colour combination to match the background.
Zigzag settings to be used for zigzag calculation and display
Oscillator settings to chose the oscillator to be used as base for 2nd zigzag
🎲 Applications
Useful in spotting divergences with both indicator and price having their own zigzag to highlight pivots
Spotting patterns in indicators/oscillators and correlate them with the patterns on price
🎲 Using External Input
If users want to use an external indicator such as OBV instead of the built in oscillators, then can do so by using the custom option.
Here is how this can be done.
Step1. Add both Dual Zigzag and the intended indicator (in this case OBV) on the chart. Notice that both OBV and Dual zigzag appear on different panes.
Step2. Edit the indicator settings of Dual zigzag and set custom indicator by selecting "custom" as oscillator name and then by setting the custom external indicator name and input.
Step 3. You would notice that the zigzag in Dual Zigzag indictor pane is already showing the zigzag pivots based on the OBV indicator and the price pivots display obv values at the pivot points. We can leave this as is.
Step 4. As an additional step, you can also merge the OBV pane and the Dual zigzag indicator pane into one by going into OBV settings and moving the indicator to above pane. Merge the scales so that there is no two scales on the same pane and the entire scale appear on the right.
At the end, you should see two panes - one with price and other with OBV and both having their zigzag plotted.
TechniTrend: Advance Custom Candle Finder (CCF)🟦 Description:
The TechniTrend: Advanced Custom Candle Finder (CCF) is a versatile tool designed to help traders identify custom candlestick patterns using various configurable criteria. This indicator provides a flexible framework to filter and highlight specific candles based on volume, volatility, candle characteristics, and other important metrics. Below is a detailed explanation of each filter and its customization options:
🟦 Volume-Based Filters
🔸Volume Spike Filter:
Enable filtering based on volume spikes. Use the Volume Spike Multiplier to define what constitutes a significant increase in volume compared to the average. A spike indicates unusually high trading interest.
🔸Volume Range Filter:
Filter candles based on specific volume ranges. Set Minimum Volume and Maximum Volume thresholds to isolate candles with trading volumes within your desired boundaries.
🟦 Candle Body & Wick Filters
🔸Body Size Filter:
Filter candles based on the size of their body. A Body Size Multiplier determines what is considered a large body relative to historical averages.
🔸Body Percentage Filter:
Filter based on the proportion of the body to the entire candle size. Use the Body Percentage Threshold to highlight candles where the body makes up a certain percentage of the total candle range.
🔸Wick-to-Body Ratio Filter:
Identify candles with specific wick-to-body ratios. A higher Wick-to-Body Ratio can indicate indecision or reversals.
🟦 Volatility & Range Filters
🔸Volatility Filter:
Highlight candles based on price changes relative to volume. The Volatility Multiplier sets the threshold for what is considered a volatile candle.
🔸Candle Range Filter:
Filter based on the range (High - Low) of each candle. Use Minimum Candle Range and Maximum Candle Range to specify your desired candle size in points or pips.
🔸Short-Term and Long-Term Volatility Filters:
Analyze volatility over different periods. Enable Short-Term Volatility or Long-Term Volatility filters to compare recent volatility against historical averages, helping you detect sudden market shifts.
🟦 Candle Color & Open/Close Filters
🔸Candle Color Filter:
Filter based on the candle's color. Choose between Bullish (close > open) or Bearish (close < open) to focus on specific market sentiments.
🔸Open/Close Price Range Filter:
Filter based on the difference between the open and close prices. Use Minimum Open/Close Range and Maximum Open/Close Range to specify your acceptable range in price movements.
🟦 Core Functionality
The CCF indicator combines these filters to provide a final signal whenever a candle meets all the enabled criteria. By default, it highlights any qualifying candle directly on the chart and changes the background color for added visibility.
🟦 Key Features:
🔸Highly Customizable Filters: Adjust the parameters for each filter to tailor the indicator to your specific needs.
🔸Multiple Conditions: Combine several conditions to identify complex candlestick patterns.
🔸Real-Time Alerts: Receive instant notifications when a matching candle pattern is found based on your custom criteria.
🟦 How to Use:
🔸Enable the filters you wish to apply (e.g., Volume Spike, Candle Body Size, Volatility).
🔸Adjust the thresholds for each filter to fine-tune the pattern recognition criteria.
🔸Observe the chart to see visual cues for candles that match your specified conditions.
🟦 Notes:
🔸Ensure that you clearly understand each filter’s role. Over-filtering with very strict criteria may reduce the number of signals.
🔸This indicator is designed to be a customizable tool, not providing buy or sell recommendations.
🔸Use in combination with other analysis tools and indicators for the best results.
Money Flow Index Crossover IndicatorThe "Money Flow Index Crossover Indicator" is a specialized technical analysis tool designed to assist traders by providing a clear visualization of potential buy and sell signals based on the Money Flow Index (MFI) and its smoothed moving average (SMA). This indicator delineates overbought and oversold zones, offering valuable insights into market dynamics. It operates as an oscillator on a separate pane, helping traders identify bullish and bearish market conditions with greater precision. By incorporating k-Nearest Neighbor (KNN) machine learning techniques, this indicator enhances the reliability and accuracy of the signals provided.
Originality and Usefulness:
This script is not just a simple mashup of existing indicators but integrates multiple components to create a unique and comprehensive analysis tool. The combined information from the MFI, its smoothed moving average, and the KNN machine learning techniques influence the form and accuracy of the Money Flow Index Average line and the Smoothed Money Flow Index line giving a visually helpful representation of overbought and oversold conditions. These lines are displayed in an oscillator style crossover, allowing users to visualize potential buy and sell zones for setting up potential signals. The user can adjust various settings of these tools behind the code to fine-tune the behavior and sensitivity of these lines. This integration provides a more robust and insightful trading tool that can adapt to different market conditions and trading styles.
How It Works:
Inputs:
MFI Settings:
Show Signals: Allows users to toggle the display of MFI and SMA crossing signals, which are critical for identifying potential market reversals.
Plot Amount: Determines the number of plots in the heat map, ranging from 2 to 28, enabling customization based on user preference.
Source: Defines the data source for MFI calculations, typically set to OHLC4 for a balanced view of price movements.
Smooth Initial MFI Length: Specifies the smoothing length for the initial MFI calculations to reduce noise and enhance signal clarity.
MFI SMA Length: Sets the length for the SMA used to smooth the MFI average, providing a more stable reference line.
Machine Learning Settings:
Use KInSource: Option to average MFI data by adding a lookback to the source, improving the accuracy of historical comparisons.
KNN Distance Requirement: Defines the distance calculation method for KNN (Max, Min, Both) to refine the data filtering process.
Machine Learning Length: Specifies the amount of machine learning data stored for smoothing results, balancing between responsiveness and stability.
KNN Length: Sets the number of KNN used to calculate the allowable distance range, enhancing the precision of the machine learning model.
Fast and Slow Lengths: Defines the lengths for fast and slow MFI calculations, allowing the indicator to capture different market dynamics.
Smoothing Length: Determines the length at which MFI calculations start for a more smoothed result, reducing false signals.
Variables and Functions:
KNN Function: Filters machine learning data to calculate valid distances based on defined criteria, ensuring more accurate MFI averages.
MFI Calculations: Computes both fast and slow MFI values, applies smoothing, and stores them for KNN processing to refine signal generation.
MFI KNN Calculation: Uses the KNN function to calculate the machine learning average of MFI values, enhancing signal reliability.
MFI Average and SMA: Calculates the average and smoothed MFI values, which are crucial for determining crossover signals.
Calculations:
MFI Values: Calculates current fast and slow MFI values and applies smoothing to reduce market noise.
Storage Arrays: Stores MFI data in arrays for KNN processing, enabling historical comparison and pattern recognition.
KNN Processing: Computes the machine learning average of MFI values using the KNN function, improving the robustness of signals.
MFI Average: Scales the MFI average to fit the heat map and calculates the smoothed SMA, providing a clear visual representation of trends.
Crossover Signals: Identifies bullish (MFI crossing above SMA) and bearish (MFI crossing below SMA) signals, which are key for making trading decisions.
Plots and Visuals:
MFI Average and SMA Lines: Plots the MFI average and smoothed SMA on the chart, allowing traders to easily visualize market trends and potential reversals.
Zones: Defines and plots overbought, neutral, and oversold zones for easy visualization. The recommended settings for these zones are:
Overbought Zone: Level set to approximately 24.6, indicating a potential market top.
Neutral Zone: Level set to 14, representing a balanced market condition.
Oversold Zone: Level set to 5.4, signaling a potential market bottom.
Crossover Marks: Plots circles on the chart to indicate bullish and bearish crossover signals, making it easier to spot entry and exit points.
Visual Alerts:
Bullish and Bearish Alerts: one can see overbought and oversold conditions and up alert conditions for bullish and bearish MFI crossover signals, enabling traders to have access to visual cues when these events are on trajectory to occur and, if they occur, act promptly with the visual representation of its zones.
Why It's Helpful:
The "Money Flow Index Crossover Indicator" provides traders with a sophisticated tool to identify potential buy and sell conditions based on the combined information of the MFI and its smoothed moving average. The KNN machine learning techniques enhance the accuracy of this indicator's clear visual representation of overbought, neutral, and oversold zones. This combination of data represented on the chart helps traders make informed decisions about market conditions. This indicator is particularly useful for traders looking to refine their entry and exit points by leveraging advanced data analysis in respect to overbought and oversold conditions.
Disclaimer:
This indicator is intended to assist traders in making informed decisions based on technical analysis. However, it is not a guarantee of future performance and should be used in conjunction with other analysis techniques and risk management practices. Past performance is not indicative of future results, and traders should exercise caution and perform their own due diligence before making any trading decisions.
Support & Resistance AI (K means/median) [ThinkLogicAI]█ OVERVIEW
K-means is a clustering algorithm commonly used in machine learning to group data points into distinct clusters based on their similarities. While K-means is not typically used directly for identifying support and resistance levels in financial markets, it can serve as a tool in a broader analysis approach.
Support and resistance levels are price levels in financial markets where the price tends to react or reverse. Support is a level where the price tends to stop falling and might start to rise, while resistance is a level where the price tends to stop rising and might start to fall. Traders and analysts often look for these levels as they can provide insights into potential price movements and trading opportunities.
█ BACKGROUND
The K-means algorithm has been around since the late 1950s, making it more than six decades old. The algorithm was introduced by Stuart Lloyd in his 1957 research paper "Least squares quantization in PCM" for telecommunications applications. However, it wasn't widely known or recognized until James MacQueen's 1967 paper "Some Methods for Classification and Analysis of Multivariate Observations," where he formalized the algorithm and referred to it as the "K-means" clustering method.
So, while K-means has been around for a considerable amount of time, it continues to be a widely used and influential algorithm in the fields of machine learning, data analysis, and pattern recognition due to its simplicity and effectiveness in clustering tasks.
█ COMPARE AND CONTRAST SUPPORT AND RESISTANCE METHODS
1) K-means Approach:
Cluster Formation: After applying the K-means algorithm to historical price change data and visualizing the resulting clusters, traders can identify distinct regions on the price chart where clusters are formed. Each cluster represents a group of similar price change patterns.
Cluster Analysis: Analyze the clusters to identify areas where clusters tend to form. These areas might correspond to regions of price behavior that repeat over time and could be indicative of support and resistance levels.
Potential Support and Resistance Levels: Based on the identified areas of cluster formation, traders can consider these regions as potential support and resistance levels. A cluster forming at a specific price level could suggest that this level has been historically significant, causing similar price behavior in the past.
Cluster Standard Deviation: In addition to looking at the means (centroids) of the clusters, traders can also calculate the standard deviation of price changes within each cluster. Standard deviation is a measure of the dispersion or volatility of data points around the mean. A higher standard deviation indicates greater price volatility within a cluster.
Low Standard Deviation: If a cluster has a low standard deviation, it suggests that prices within that cluster are relatively stable and less likely to exhibit sudden and large price movements. Traders might consider placing tighter stop-loss orders for trades within these clusters.
High Standard Deviation: Conversely, if a cluster has a high standard deviation, it indicates greater price volatility within that cluster. Traders might opt for wider stop-loss orders to allow for potential price fluctuations without getting stopped out prematurely.
Cluster Density: Each data point is assigned to a cluster so a cluster that is more dense will act more like gravity and
2) Traditional Approach:
Trendlines: Draw trendlines connecting significant highs or lows on a price chart to identify potential support and resistance levels.
Chart Patterns: Identify chart patterns like double tops, double bottoms, head and shoulders, and triangles that often indicate potential reversal points.
Moving Averages: Use moving averages to identify levels where the price might find support or resistance based on the average price over a specific period.
Psychological Levels: Identify round numbers or levels that traders often pay attention to, which can act as support and resistance.
Previous Highs and Lows: Identify significant previous price highs and lows that might act as support or resistance.
The key difference lies in the approach and the foundation of these methods. Traditional methods are based on well-established principles of technical analysis and market psychology, while the K-means approach involves clustering price behavior without necessarily incorporating market sentiment or specific price patterns.
It's important to note that while the K-means approach might provide an interesting way to analyze price data, it should be used cautiously and in conjunction with other traditional methods. Financial markets are influenced by a wide range of factors beyond just price behavior, and the effectiveness of any method for identifying support and resistance levels should be thoroughly tested and validated. Additionally, developments in trading strategies and analysis techniques could have occurred since my last update.
█ K MEANS ALGORITHM
The algorithm for K means is as follows:
Initialize cluster centers
assign data to clusters based on minimum distance
calculate cluster center by taking the average or median of the clusters
repeat steps 1-3 until cluster centers stop moving
█ LIMITATIONS OF K MEANS
There are 3 main limitations of this algorithm:
Sensitive to Initializations: K-means is sensitive to the initial placement of centroids. Different initializations can lead to different cluster assignments and final results.
Assumption of Equal Sizes and Variances: K-means assumes that clusters have roughly equal sizes and spherical shapes. This may not hold true for all types of data. It can struggle with identifying clusters with uneven densities, sizes, or shapes.
Impact of Outliers: K-means is sensitive to outliers, as a single outlier can significantly affect the position of cluster centroids. Outliers can lead to the creation of spurious clusters or distortion of the true cluster structure.
█ LIMITATIONS IN APPLICATION OF K MEANS IN TRADING
Trading data often exhibits characteristics that can pose challenges when applying indicators and analysis techniques. Here's how the limitations of outliers, varying scales, and unequal variance can impact the use of indicators in trading:
Outliers are data points that significantly deviate from the rest of the dataset. In trading, outliers can represent extreme price movements caused by rare events, news, or market anomalies. Outliers can have a significant impact on trading indicators and analyses:
Indicator Distortion: Outliers can skew the calculations of indicators, leading to misleading signals. For instance, a single extreme price spike could cause indicators like moving averages or RSI (Relative Strength Index) to give false signals.
Risk Management: Outliers can lead to overly aggressive trading decisions if not properly accounted for. Ignoring outliers might result in unexpected losses or missed opportunities to adjust trading strategies.
Different Scales: Trading data often includes multiple indicators with varying units and scales. For example, prices are typically in dollars, volume in units traded, and oscillators have their own scale. Mixing indicators with different scales can complicate analysis:
Normalization: Indicators on different scales need to be normalized or standardized to ensure they contribute equally to the analysis. Failure to do so can lead to one indicator dominating the analysis due to its larger magnitude.
Comparability: Without normalization, it's challenging to directly compare the significance of indicators. Some indicators might have a larger numerical range and could overshadow others.
Unequal Variance: Unequal variance in trading data refers to the fact that some indicators might exhibit higher volatility than others. This can impact the interpretation of signals and the performance of trading strategies:
Volatility Adjustment: When combining indicators with varying volatility, it's essential to adjust for their relative volatilities. Failure to do so might lead to overemphasizing or underestimating the importance of certain indicators in the trading strategy.
Risk Assessment: Unequal variance can impact risk assessment. Indicators with higher volatility might lead to riskier trading decisions if not properly taken into account.
█ APPLICATION OF THIS INDICATOR
This indicator can be used in 2 ways:
1) Make a directional trade:
If a trader thinks price will go higher or lower and price is within a cluster zone, The trader can take a position and place a stop on the 1 sd band around the cluster. As one can see below, the trader can go long the green arrow and place a stop on the one standard deviation mark for that cluster below it at the red arrow. using this we can calculate a risk to reward ratio.
Calculating risk to reward: targeting a risk reward ratio of 2:1, the trader could clearly make that given that the next resistance area above that in the orange cluster exceeds this risk reward ratio.
2) Take a reversal Trade:
We can use cluster centers (support and resistance levels) to go in the opposite direction that price is currently moving in hopes of price forming a pivot and reversing off this level.
Similar to the directional trade, we can use the standard deviation of the cluster to place a stop just in case we are wrong.
In this example below we can see that shorting on the red arrow and placing a stop at the one standard deviation above this cluster would give us a profitable trade with minimal risk.
Using the cluster density table in the upper right informs the trader just how dense the cluster is. Higher density clusters will give a higher likelihood of a pivot forming at these levels and price being rejected and switching direction with a larger move.
█ FEATURES & SETTINGS
General Settings:
Number of clusters: The user can select from 3 to five clusters. A good rule of thumb is that if you are trading intraday, less is more (Think 3 rather than 5). For daily 4 to 5 clusters is good.
Cluster Method: To get around the outlier limitation of k means clustering, The median was added. This gives the user the ability to choose either k means or k median clustering. K means is the preferred method if the user things there are no large outliers, and if there appears to be large outliers or it is assumed there are then K medians is preferred.
Bars back To train on: This will be the amount of bars to include in the clustering. This number is important so that the user includes bars that are recent but not so far back that they are out of the scope of where price can be. For example the last 2 years we have been in a range on the sp500 so 505 days in this setting would be more relevant than say looking back 5 years ago because price would have to move far to get there.
Show SD Bands: Select this to show the 1 standard deviation bands around the support and resistance level or unselect this to just show the support and resistance level by itself.
Features:
Besides the support and resistance levels and standard deviation bands, this indicator gives a table in the upper right hand corner to show the density of each cluster (support and resistance level) and is color coded to the cluster line on the chart. Higher density clusters mean price has been there previously more than lower density clusters and could mean a higher likelihood of a reversal when price reaches these areas.
█ WORKS CITED
Victor Sim, "Using K-means Clustering to Create Support and Resistance", 2020, towardsdatascience.com
Chris Piech, "K means", stanford.edu
█ ACKNOLWEDGMENTS
@jdehorty- Thanks for the publish template. It made organizing my thoughts and work alot easier.
FRAMA and Candlestick Patterns [CSM]FRAMA (Fractal Adaptive Moving Average) is a technical analysis indicator that adapts its smoothing period according to the market's volatility, allowing it to provide accurate signals in all market conditions. This indicator script plots the FRAMA on a chart and generates buy and sell signals based on the FRAMA and candlestick patterns. It also includes an option to filter signals based on bullish and bearish engulfing patterns.
To detect candlestick patterns, the script imports the "BankNifty_CSM" library from the creator's public library on TradingView. The FRAMA calculation is done using a loop that iterates over the last "length" number of bars, with the smoothing factor adjusted based on the "fracDim" parameter.
The buy and sell signals are generated based on the position of the current price relative to the FRAMA line. If the "engulfing" parameter is set to true, the signals are further filtered based on bullish and bearish engulfing patterns.
Overall, this script combines various technical indicators and candlestick pattern recognition to provide a complete trading strategy. However, as with any trading strategy, it should be thoroughly backtested and evaluated before using it in a live trading environment.
SubCandleI created this script as POC to handle specific cases where not having tick data on historical bars create repainting. Happy to share if this serves purpose for other coders.
What is the function of this script?
Script plots a sub-candle which is remainder of candle after forming the latest peak.
Higher body of Sub-candle refers to strong retracement of price from its latest peak. Color of the sub-candle defines the direction of retracement.
Higher wick of Sub-candle refers to higher push in the direction of original candle. Meaning, after price reaching its peak, price retraced but could not hold.
Here is a screenshot with explanation to visualise the concept:
Settings
There is only one setting which is number of backtest bars. Lower timeframe resolution which is used for calculating the Sub-candle uses this number to automatically calculate maximum possible lower timeframe so that all the required backtest windows are covered without having any issue.
We need to keep in mind that max available lower timeframe bars is 100,000. Hence, with 5000 backtest bars, lower timeframe resolution can be about 20 (100000/5000) times lesser than that of regular chart timeframe. We need to also keep in mind that minimum resolution available as part of security_lower_tf is 1 minute. Hence, it is not advisable to use this script for chart timeframes less than 15 mins.
Application
I have been facing this issue in pattern recognition scripts where patterns are formed using high/low prices but entry and targets are calculated based on the opposite side (low/high). It becomes tricky during extreme bars to identify entry conditions based on just the opposite peak because, the candle might have originated from it before identifying the pattern and might have never reached same peak after forming the pattern. Due to lack of tick data on historical bars, we cannot use close price to measure such conditions. This leads to repaint and few unexpected results. I am intending to use this method to overcome the issue up-to some extent.
Zig Zag High LowZig Zag script that uses local minimums and maximums as pivot points. It can be used as a source for pattern recognition.
Fractal Breakout V2Version 2 of my fractal pattern aid ( Version 1 ).
I added a bouncing line between the high and low trend lines, connecting consecutive extreme points. I also chased down a pesky bug in the slope calculation...and for now I have disabled the ability to change resolution basis for extreme detection (e.g. 30m on a 1hr chart).
For fun, I added some shading to make it more apparent at a glance what is happening, but if you find it gimmicky, there's an option to turn that off.
I am inexperienced with pattern recognition, so please send feedback if you have any ideas that would make this more useful.
Thanks!
Lemrin
Historical Volatility Strategy Backtest Strategy buy when HVol above BuyBand and close position when HVol below CloseBand.
Markets oscillate from periods of low volatility to high volatility
and back. The author`s research indicates that after periods of
extremely low volatility, volatility tends to increase and price
may move sharply. This increase in volatility tends to correlate
with the beginning of short- to intermediate-term moves in price.
They have found that we can identify which markets are about to make
such a move by measuring the historical volatility and the application
of pattern recognition.
The indicator is calculating as the standard deviation of day-to-day
logarithmic closing price changes expressed as an annualized percentage.
Please, use it only for learning or paper trading. Do not for real trading.
Historical Volatility Strategy Strategy buy when HVol above BuyBand and close position when HVol below CloseBand.
Markets oscillate from periods of low volatility to high volatility
and back. The author`s research indicates that after periods of
extremely low volatility, volatility tends to increase and price
may move sharply. This increase in volatility tends to correlate
with the beginning of short- to intermediate-term moves in price.
They have found that we can identify which markets are about to make
such a move by measuring the historical volatility and the application
of pattern recognition.
The indicator is calculating as the standard deviation of day-to-day
logarithmic closing price changes expressed as an annualized percentage.
Historical Volatility Markets oscillate from periods of low volatility to high volatility
and back. The author`s research indicates that after periods of
extremely low volatility, volatility tends to increase and price
may move sharply. This increase in volatility tends to correlate
with the beginning of short- to intermediate-term moves in price.
They have found that we can identify which markets are about to make
such a move by measuring the historical volatility and the application
of pattern recognition.
The indicator is calculating as the standard deviation of day-to-day
logarithmic closing price changes expressed as an annualized percentage.
Scalp Precision Matrix [BullByte]SCALP PRECISION MATRIX (SPM)
OVERVIEW
Scalp Precision Matrix (SPM) is a comprehensive decision-support framework designed specifically for scalpers and short-term traders. This indicator synthesizes five distinct analytical layers into a unified system that helps identify high-quality setups while avoiding common pitfalls that trap traders.
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THE CORE PROBLEM THIS INDICATOR ADDRESSES
Scalping demands rapid decision-making while simultaneously processing multiple data points. Traders constantly ask themselves: Is momentum still alive? Am I entering near a potential reversal zone? Is this the right session to trade? What is my actual risk-to-reward? Most traders either overwhelm themselves with too many separate indicators (creating analysis paralysis) or use too few (missing crucial context).
SPM was developed to consolidate these essential checks into one cohesive framework. Rather than overlaying disconnected indicators, each component in SPM directly informs and adjusts the others, creating an integrated analytical system.
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WHY THESE SPECIFIC COMPONENTS AND HOW THEY WORK TOGETHER
The five analytical layers in SPM are not arbitrarily combined. Each addresses a specific question in the scalping decision process, and together they form a logical workflow:
LAYER 1: MOMENTUM FUEL GAUGE
This answers the question: "Does the current move still have energy?"
After any impulse move (a significant directional price movement), momentum naturally decays over time. The Fuel Gauge estimates remaining momentum by analyzing four factors:
Body Strength (30% weight): Compares recent candle body sizes against the historical average. Strong momentum produces candles with large bodies relative to their wicks. The calculation takes the 3-bar average body size divided by the 20-bar average body size, then scales it to a 0-100 range.
Wick Rejection (25% weight): Measures the wick-to-body ratio. When wicks are large relative to bodies, it suggests rejection and weakening momentum. A ratio of 2.0 or higher (wicks twice the body size) scores low; smaller ratios score higher.
Volume Consistency (20% weight): Compares recent 3-bar average volume against the lookback period average. Sustained moves require consistent volume support. Volume dropping off suggests the move may be losing participation.
Time Decay (25% weight): Tracks how many bars have passed since the last detected impulse. Momentum naturally fades over time. The typical impulse duration is adjusted based on the current volatility regime.
These components are weighted and combined, then smoothed with a 3-period EMA to reduce noise. The result is a 0-100% gauge where:
- Above 70% = Strong momentum (green)
- 40-70% = Moderate momentum (amber)
- Below 40% = Weak momentum (red)
- Below 20% = Exhausted (triggers EXIT warning)
The Fuel Gauge also estimates how many bars of momentum remain based on the current burn rate.
IMPORTANT DISCLAIMER : The Fuel Gauge is NOT order flow, volume profile, or depth of market data. It is a technical proxy calculated entirely from standard OHLCV (Open, High, Low, Close, Volume) data. The term "Fuel" is used metaphorically to represent estimated remaining momentum energy.
LAYER 2: TRAP ZONE DETECTION
This answers the question: "Am I walking into a potential reversal area?"
Price tends to reverse at levels where it has reversed before. SPM identifies these zones by detecting clusters of historical swing points:
How it works:
1. The indicator detects swing highs and swing lows using the Swing Detection Length setting (default 5 bars on each side required to confirm a pivot).
2. Recent swing points are stored (up to 10 of each type).
3. For each potential zone, the algorithm counts how many swing points cluster within a tolerance of 0.5 ATR.
4. Zones with 2 or more clustered swing points, positioned between 0.3 and 4.0 ATR from current price, are marked as Trap Zones.
5. A Confluence Score is calculated based on cluster density and proximity to current price.
The percentage displayed (e.g., "TRAP 85%") is a CONFLUENCE SCORE, not a probability. Higher percentages mean more swing points cluster at that level and price is closer to it. This indicates stronger historical significance, not a prediction of future reversal.
CRITICAL DISCLAIMER : Trap Zones are NOT institutional order flow, liquidity pools, smart money footprints, or any proprietary data feed. They are calculated purely from historical swing point clustering using standard technical analysis. The term "trap" describes how price action has historically reversed at these levels, potentially trapping traders who enter prematurely. This is pattern recognition, not market structure data.
LAYER 3: VELOCITY ANALYSIS
This answers the question: "Is price moving favorably right now?"
Velocity measures how fast price is currently moving compared to its recent average:
Calculation:
- Current velocity = Absolute price change from previous bar divided by ATR
- Average velocity = Simple moving average of velocity over the lookback period
- Velocity ratio = Current velocity divided by average velocity
Classification:
- FAST (ratio above 1.5 ): Price is moving significantly faster than normal. Good for momentum continuation plays.
- NORMAL (ratio 0.5 to 1.5) : Typical price movement speed.
- SLOW (ratio below 0.5 ): Price is moving sluggishly. Often indicates ranging or choppy conditions where scalping becomes difficult.
The velocity score contributes 18% to the overall quality score calculation.
LAYER 4: SESSION AWARENESS
This answers the question: "Is this a good time to trade?"
Different trading sessions have different characteristics. SPM automatically detects which major session is active and adjusts its quality assessment:
Session Times (all in UTC):
- A sia Session : 00:00 - 08:00 UTC
- London Session : 08:00 - 16:00 UTC
- New York Session : 13:00 - 21:00 UTC
- London/NY Overlap : 13:00 - 16:00 UTC
- Off-Peak : Outside major sessions
Session Quality Weighting:
- Overlap : 100 points (highest liquidity, best movement)
- London : 85 points
- New York : 80 points
- Asia : 50 points (tends to range more)
- Off-Peak : 30 points (lower liquidity, more false signals)
The session score contributes 17% to the overall quality calculation. Signals are also filtered to prevent firing during off-peak hours.
Note : These are fixed UTC times and may not perfectly match your broker's session boundaries. Use them as general guidance rather than precise timing.
LAYER 5: VOLATILITY REGIME ADAPTATION
This answers the question: "How should I adjust for current market conditions?"
SPM compares current volatility (14-period ATR) against historical volatility (50-period ATR) to categorize the market:
HIGH Volatility (ratio above 1.3): Current ATR is 30%+ above normal. SPM widens thresholds to filter noise and extends target projections.
NORMAL Volatility (ratio 0.7 to 1.3): Typical conditions. Standard parameters apply.
LOW Volatility (ratio below 0.7): Current ATR is 30%+ below normal. SPM tightens thresholds for sensitivity and reduces target expectations. The market state may show AVOID during prolonged low volatility.
This adaptation prevents false signals during erratic markets and missed signals during quiet markets.
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THE SYNERGY: WHY THIS COMBINATION MATTERS
These five layers are not independent indicators placed on one chart. They form an interconnected system:
- A signal only fires when momentum exists (Fuel above 40%), price is away from danger zones (Trap Zones factored into quality score), movement is favorable (Velocity contributes to score), timing is appropriate (Session is not off-peak), and volatility is accounted for (thresholds adapt to regime).
- The Trap Zones directly influence Entry Zone placement. Entry zones are positioned beyond trap zones to avoid getting caught in reversals.
- Target projections automatically adjust to avoid placing take-profit levels inside detected trap zones.
- The Fuel Gauge affects which signal tier fires. Insufficient fuel prevents all signals.
- Session quality is weighted into the overall score, reducing signal quality during less favorable trading hours.
This integration is the core originality of SPM. Each component makes the others more useful than they would be in isolation.
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HOW THE QUALITY SCORE IS CALCULATED
The Quality Score (0-100) synthesizes all layers into a single number for each direction (long and short):
For Long Quality Score:
- Fuel Component (28% weight) : Full fuel value if impulse direction is bullish; 60% of fuel value otherwise
- Trap Avoidance (22% weight) : 75 points if no trap zone below; otherwise 100 minus the trap confluence score (minimum 20)
- Velocity Component (18% weight) : Direct velocity score
- Session Component (17% weight) : Current session quality score
- Trend Alignment (15% bonus) : Adds 12 points if price is above the 20-period SMA
For Short Quality Score:
- Same structure but reversed (bearish impulse direction, trap zone above, price below SMA)
The direction with the higher score becomes the current Bias. A 12-point difference is required to switch bias, preventing flip-flopping in neutral conditions.
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SIGNAL TYPES AND WHAT THEY MEAN
SPM generates four types of signals, each with specific visual representation:
PRIME SIGNALS (Cyan Diamond)
These represent the highest quality confluence. Requirements:
- Quality score crosses above the Prime threshold (default 80)
- Bias aligns with signal direction
- Fuel is sufficient (above 40%)
- Session is active (not off-peak)
- Cooldown period has passed
Prime signals appear as cyan-colored diamond shapes. Long signals appear below the bar; short signals appear above.
STANDARD SIGNALS (Green Triangle Up / Red Triangle Down)
These represent good quality setups. Requirements:
- Quality score crosses above the Standard threshold (default 75) but below Prime
- Same bias, fuel, and cooldown requirements as Prime
Standard signals appear as small triangles in green (long) or red (short).
CAUTION SIGNALS (Small Faded Circle)
These represent minimum threshold setups. Requirements:
- Quality score crosses above the Caution threshold (default 65) but below Standard
- Same additional requirements
Caution signals appear as small, faded circles. These suggest the setup exists but with weaker confluence. Consider these only when broader market context supports them, or skip them entirely during uncertain conditions.
EXHAUSTION SIGNAL (Purple X with "EXIT" text)
This warning appears when the Fuel Gauge drops below 20% from above, indicating momentum has depleted. This is not a trade signal but a warning to:
- Consider exiting existing positions
- Avoid entering new trades in the current direction
- Wait for new momentum to develop
All signals use CONFIRMED bar data only (referencing the previous closed bar) to prevent repainting. Once a signal appears, it will never disappear or change position on historical bars.
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READING THE CHART ELEMENTS
TRAP ZONES (Red Dashed Box with "TRAP XX%" Label)
These mark price levels where multiple historical swing points cluster. The red dashed box shows the zone boundaries. The percentage is the confluence score indicating cluster strength and proximity.
How to use: When price approaches a trap zone, be cautious about entering in that direction. If your bias is LONG and there's a strong trap zone above, consider taking partial profits before price reaches it or adjusting your target below it.
ENTRY ZONES (Green Solid Box with "ENTRY" Label)
These show suggested entry areas based on the current bias direction. For LONG bias, the entry zone appears below the trap zone (buying the dip beyond support). For SHORT bias, it appears above the trap zone (selling the rally beyond resistance).
How to use: Rather than entering at current price, consider placing limit orders within the entry zone. This positions you beyond where typical trap reversals occur.
TARGET ZONES (Blue Dotted Box with "TARGET" Label)
These project potential take-profit areas based on ATR multiples, adjusted for:
- Current volatility regime (wider in high volatility, tighter in low)
- Impulse direction (larger targets when aligned with impulse)
- Nearby trap zones (targets adjust to avoid placing TP inside trap zones)
How to use: These are suggestions, not guarantees. Consider taking partial profits before the target or using trailing stops once price moves favorably.
STOP LEVEL (Orange Dashed Line with "STOP" Label)
This shows suggested stop-loss placement, calculated as 0.8 ATR beyond the trap zone (or 2.0 ATR from current price if no trap zone exists).
How to use: This provides a reference for risk calculation. The dashboard R:R ratio is calculated using this stop level.
Chart Example: Scalp Precision Matrix displays real-time market analysis through dynamic zones and quality scores. ENTRY/TARGET/STOP zones show potential price levels based on current market structure - they appear continuously as reference points, NOT as trade instructions. Actual trade signals (diamonds, triangles, circles) fire only when multiple conditions align: quality score thresholds are crossed, fuel gauge is sufficient, session is active, and cooldown period has passed. The zones help you understand market context; the signals tell you when to act.
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UNDERSTANDING THE DASHBOARD (Top Right Panel)
The main dashboard provides comprehensive market context:
Row 1 - Header:
- "SPM " : Indicator name
- Market State : Current overall condition
Market States Explained:
- PRIME : Excellent conditions. Quality score meets prime threshold, session is active. Best opportunities.
- READY : Good conditions. Quality score meets standard threshold. Solid setups available.
- WAIT : Mixed conditions. Some factors favorable, others not. Patience recommended.
- AVOID : Poor conditions. Off-peak session or very low volatility. High risk of false signals.
- EXIT : Fuel exhausted. Momentum depleted. Consider closing positions or waiting.
Row 2-3 - Quality Bars:
- " UP ########## " : Visual meter for long quality (each # = 10 points, . = empty)
- " DN ########## " : Visual meter for short quality
- The number on the right shows the exact quality score
Row 4 - Bias:
- Shows current directional lean: LONG, SHORT, or NEUTRAL
- Color-coded: Green for long, red for short, gray for neutral
Rows 5-7 (Full Mode Only) - Trade Levels:
- Entry : Suggested entry price for current bias direction
- Stop : Suggested stop-loss price
- Target : Projected take-profit price
Row 8 - Risk:Reward Ratio:
- Format : "1:X.X" where X.X is the reward multiple
- Color-coded : Green if 2:1 or better, amber if 1.5:1 to 2:1, red if below 1.5:1
Row 9 - Fuel:
- Shows percentage and estimated bars remaining in parentheses
- Example : "72% (8)" means 72% fuel with approximately 8 bars remaining
- Color-coded : Green above 70%, amber 40-70%, red below 40%
Row 10-11 (Full Mode Only) - Market Conditions:
- Vol : Current volatility regime (HIGH/NORMAL/LOW)
- Speed : Current velocity zone (FAST/NORMAL/SLOW)
Row 12 - Session:
- Shows active trading session
- Color-coded by session type
Row 13 (Full Mode Only) - Remaining:
- Time remaining in current session (hours and minutes)
Row 14 (Conditional) - Trap Warning:
- Appears when a significant trap zone exists in your bias direction
- Shows direction (ABOVE/BELOW) and confluence percentage
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UNDERSTANDING THE QUICK PANEL (Bottom Left)
The Quick Panel provides essential information at a glance without looking away from price action:
Row 1: Current Bias and Quality Score (large text for quick reading)
Row 2: Market State
Row 3: Fuel Percentage
Row 4: Estimated Bars Remaining
Row 5: Risk:Reward Ratio
Row 6: Current Session
Both panels can be repositioned using the settings, and each can be toggled on/off independently.
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SETTINGS EXPLAINED
CORE SETTINGS:
Analysis Lookback (Default: 20)
Number of bars used for statistical calculations including average volume and average body size. Higher values create smoother but slower-reacting analysis. Lower values are more responsive but may include more noise.
Swing Detection Length (Default: 5)
Bars required on each side to confirm a swing high or low. A setting of 5 means a swing high must have 5 lower highs on each side. Lower values detect more swings (more trap zones, more sensitivity). Higher values find only major pivots (fewer but more significant zones).
Impulse Sensitivity (Default: 1.5)
Multiplier for ATR when detecting impulse moves. Lower values (like 1.0) detect smaller price movements as impulses, refreshing the fuel gauge more frequently. Higher values (like 2.5) require larger moves, making impulse detection less frequent but more significant.
SIGNAL SETTINGS:
Prime/Standard/Caution Thresholds (Defaults: 80/75/65)
These control the quality score required for each signal tier. You can adjust these based on your preference:
- More conservative : Raise thresholds (e.g., 85/80/70) for fewer but higher-quality signals
- More aggressive : Lower thresholds (e.g., 75/70/60) for more signals with slightly lower quality
Signal Cooldown (Default: 8 bars)
Minimum bars between signals to prevent signal spam. After any signal fires, no new signals can appear until this many bars pass. Increase for fewer signals in choppy markets; decrease if you want faster signal refresh.
Show Prime/Standard/Caution/Exhaustion Signals
Toggle each signal type on or off based on your preference.
ZONE DISPLAY:
Show Trap Zones / Entry Zones / Target Zones / Stop Levels
Toggle each zone type on or off. Turning off zones you don't use reduces chart clutter.
Zone Transparency (Default: 88)
Controls how transparent zone boxes appear. Higher values (closer to 95) make zones barely visible; lower values (closer to 75) make them more prominent.
Zone History (Default: 25 bars)
How far back zone boxes extend on the chart. Purely visual preference.
BACKGROUND:
Background Mode (Options: Off, Subtle, Normal)
Controls whether and how intensely the chart background is colored. Subtle is barely noticeable; Normal is more visible; Off disables background coloring entirely.
Background Type (Options: Bias, Fuel)
- Bias : Colors background based on current directional lean (green for long, red for short)
- Fuel : Colors background based on momentum level (green for high fuel, amber for moderate, red for low)
DASHBOARD / QUICK PANEL:
Show Dashboard / Show Quick Panel
Toggle each panel on or off.
Compact Mode
When enabled, the main dashboard shows only essential rows (quality bars, bias, R:R, fuel, session) without entry/stop/target levels, volatility, velocity, or time remaining.
Position Settings
Choose where each panel appears on your chart from six options: Top Right, Top Left, Bottom Right, Bottom Left, Middle Right, Middle Left.
ALERTS:
Alert Prime Signals / Standard Signals / Fuel Exhaustion
Enable or disable TradingView alerts for each condition. When enabled, you can set up alerts in TradingView that will notify you when these conditions occur.
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RECOMMENDED TIMEFRAMES AND USAGE
OPTIMAL TIMEFRAMES:
- 1-minute to 5-minute : Best for active scalping with quick entries and exits
- 5-minute to 15-minute : Balanced scalping with slightly more confirmation
- 15-minute to 1-hour : Short-term swing entries, fewer but more significant signals
Zone visualizations only appear on intraday timeframes to prevent chart clutter on higher timeframes.
BEST PRACTICES:
1. Trade primarily during LONDON, NEW YORK, or OVERLAP sessions. The indicator weights these sessions higher for good reason - liquidity and movement are typically better.
2. Prioritize PRIME signals. These represent the highest confluence and have proven most reliable. Use STANDARD signals as secondary opportunities. Treat CAUTION signals with extra scrutiny.
3. Respect the Fuel Gauge. Avoid entering new positions when fuel is below 40%. When the EXIT signal appears, seriously consider closing or reducing positions.
4. Pay attention to TRAP warnings. When the dashboard shows a trap zone in your bias direction, be cautious about holding through that level.
5. Verify R:R before entry. The dashboard shows the risk-to-reward ratio. Ensure it meets your minimum requirements (many traders require at least 1.5:1 or 2:1).
6. When state shows AVOID or EXIT, step back. These conditions typically produce poor results.
7. Combine with your own analysis. SPM is a decision-support tool, not a standalone system. Use it alongside your understanding of market structure, news events, and overall context.
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PRACTICAL EXAMPLE
Scenario : You're watching a 5-minute chart during London session. A cyan diamond (Prime Long signal) appears below the bar.
Before entering, you check the dashboard:
- State shows "PRIME" - conditions are favorable
- Fuel shows "72% (8)" - plenty of momentum remaining (approximately 8 bars)
- R:R shows "1:2.3" - acceptable risk-to-reward ratio
- Session shows "LONDON" - active session with good liquidity
- No TRAP warning in dashboard - no immediate resistance cluster in your way
- Entry zone visible on chart at a lower price level
- Stop and Target zones clearly marked
With this confluence of factors, you have context for a more informed decision. The signal indicates quality, the fuel suggests momentum remains, the R:R is favorable, and no immediate trap threatens your trade.
However, you also notice the target zone sits just below where a trap zone would be if there were one. This is by design - SPM adjusts targets to avoid placing them inside reversal zones.
This multi-factor confirmation delivered in a single glance is what SPM provides.
Chart Example :This chart demonstrates how the Scalp Precision Matrix identifies key market transitions. After a strong bullish impulse (cyan PRIME signal at ~08:30), price reached a historical reversal cluster (TRAP ZONE at 92,300). The indicator detected momentum exhaustion (purple EXIT signal) as fuel dropped below 20%, warning traders to exit longs. Now showing a SHORT bias with entry/stop/target zones clearly marked. The 92% trap zone confluence indicates a strong cluster of previous swing highs where price historically reversed.
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DATA WINDOW VALUES
For detailed analysis and strategy development, SPM exports the following values to TradingView's Data Window (visible when you hover over the chart with the indicator selected):
- Long Quality Score (0-100)
- Short Quality Score (0-100)
- Fuel Gauge (0-100%)
- Risk:Reward Ratio
These values can be useful for understanding how the indicator behaves over time and for developing your own insights about when it works best for your trading style.
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NON-REPAINTING CONFIRMATION
All signals in SPM are generated using CONFIRMED bar data only. The signal logic references the previous closed bar's values ( and in Pine Script terms). This means:
- Signals appear at the OPEN of the new bar (after the previous bar closes)
- Signals will NEVER disappear once they appear
- Signals will NEVER change position on historical bars
- What you see in backtesting is what you would have seen in real-time
The dashboard and zones update in real-time to provide current market context, but the trading signals themselves are non-repainting.
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IMPORTANT DISCLAIMERS
TERMINOLOGY CLARIFICATION:
This indicator uses terms that might imply access to data it does not have. To be completely transparent:
- "Trap Zones" are calculated from historical swing point clustering. They are NOT institutional liquidity pools, order blocks, smart money footprints, or any form of order flow data. The term "trap" is metaphorical, describing how price has historically reversed at these levels.
- "Fuel Gauge" is a technical momentum proxy. It is NOT order flow, volume profile, depth of market, or bid/ask data. It estimates momentum remaining based entirely on standard OHLCV price and volume data.
- "Quality Scores" are weighted combinations of the technical factors described above. A high score indicates multiple conditions align favorably according to the indicator's logic. It does NOT predict or guarantee trade success.
- The percentages shown on trap zones are CONFLUENCE SCORES measuring cluster density and proximity. They are NOT probability predictions of reversal.
TRADING RISK WARNING:
Trading involves substantial risk of loss and is not suitable for all investors. This indicator is a technical analysis tool designed to assist with decision-making. It does not constitute financial advice, trading advice, or any other sort of advice. Past performance of any signal or pattern does not guarantee future results. Markets are inherently unpredictable.
Always use proper risk management. Define your risk before entering any trade. Never risk more than you can afford to lose. Consider consulting with a licensed financial advisor before making trading decisions.
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ORIGINALITY STATEMENT - NOT A MASHUP
Scalp Precision Matrix is an original work that combines several analytical concepts into a purpose-built scalping framework. While individual components like ATR calculations, pivot detection, session timing, and trend alignment exist in various forms elsewhere, the specific implementation here represents original synthesis:
- The Fuel Gauge decay model with its four-component weighted calculation
- The Trap Zone cluster detection with confluence scoring
- The multi-factor quality scoring system that integrates all layers
- The trap-aware entry and target zone placement logic
- The volatility regime adaptation across all components
- The session weighting is integrated into the quality assessment
The indicator does not simply overlay separate indicators on one chart. It creates interconnected layers where each component informs and adjusts the others. This integration is the core originality of SPM.
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For best results, combine SPM with your own market understanding and always practice proper risk management.
-BullByte
Candlestick Pattern Scanner Pro hybrid strategy that combines candlestick pattern recognition with order flow analysis for high-probability scalping entries
Top-Down Analysis - Multi-Timeframe AlignmentThis indicator implements a Top-Down Multi-Timeframe Trading Analysis System. Here's what it does:
Core Functionality
1. Multi-Timeframe Bias Detection
Monitors three timeframes: Daily, 4-Hour, and 1-Hour
Determines if each timeframe is bullish, bearish, or neutral based on two EMAs (9 and 21 period by default)
A timeframe is bullish when: Fast EMA > Slow EMA AND price is above Fast EMA
A timeframe is bearish when: Fast EMA < Slow EMA AND price is below Fast EMA
2. Alignment Tier System
Tier 1 (Full Alignment): All three timeframes agree (Daily = 4H = 1H direction)
Tier 2 (Partial Alignment): Daily and 1H agree, but 4H differs
No Alignment: Timeframes disagree
3. Previous Day Support & Resistance Levels
Automatically plots key levels from the previous day:
Previous Day High (PDH) - resistance
Previous Day Low (PDL) - support
Previous Day Close (PDC)
Previous Day Midpoint (PDM)
4. Execution Zone (15-Minute Window)
Highlights the first 15 minutes after each new 4H candle opens
This is the optimal entry window when alignment conditions are met
5. Pattern Recognition
Detects trading setups:
Double tops/bottoms
Long wicks at support/resistance
Bullish/bearish closes aligned with bias
6. Trade Signals
Generates entry signals when:
There's Tier 1 or Tier 2 alignment
Price is in the 15-minute execution zone
A valid pattern forms (double top/bottom or wick rejection)
7. Visual Dashboard
Shows a real-time table with:
Each timeframe's current bias
Alignment status
Next 4H prediction
Whether price is at a key support/resistance level
Trading Strategy
The indicator helps traders follow the principle of "trade with the higher timeframe trend" by only taking trades when multiple timeframes agree, focusing entries during specific windows, and respecting previous day's key price levels as potential reaction zones.
88-Key Piano Range - Musical Price Levels88-Key Piano Range - Musical Price Levels
Description:
Explore price analysis through musical harmony! This educational indicator maps price movements to the standard 88-key piano keyboard (A0 to C8), offering a creative way to visualize market ranges and explore harmonic price relationships with authentic keyboard-style background fills.
🎹 KEY FEATURES:
• Complete 88-Key Mapping - Full piano range from A0 to C8 mapped to your price range
• Piano-Style Visual Design - Clean background fills distinguishing white keys, black keys, and octaves
• Dual Anchor System - Set two time/price points to define your analytical range
• Flexible Display Options - Show all 88 keys, octaves only (C notes), or custom selections
• Harmonic Exploration - Explore consonant/dissonant key relationships based on music theory
• Real-time Price Note - See what musical note your current price represents
• Customizable Interface - Adjust colors, line widths, fills, and visual elements
🎵 EDUCATIONAL CONCEPTS:
• Octave Levels - C notes as harmonic reference points (similar to round numbers)
• Key Classifications - Natural notes (white keys) vs chromatic notes (black keys)
• Harmonic Intervals - Musical relationships applied to price analysis
• Creative Visualization - Alternative way to view price ranges and movements
⚙️ HOW TO USE:
1. Select Your Price Leg - Choose an upleg, downleg, or significant price movement to explore
2. Set Anchor A - Place at the start of your selected leg (swing low for upleg, swing high for downleg)
3. Set Anchor B - Place at the end of your selected leg (swing high for upleg, swing low for downleg)
4. Configure Display - Select all keys, octaves only, or enable background fills
5. Explore Harmonics - Enable harmony coloring to see musical relationships
6. Study Patterns - Observe how price movements align with musical intervals
🎼 CREATIVE APPLICATIONS:
• Experimental Analysis - Try a musical approach to leg analysis
• Educational Tool - Learn about mathematical relationships in both music and markets
• Alternative Perspective - View support/resistance through a musical lens
• Pattern Recognition - Explore if harmonic levels show interesting price behavior
• Fun Learning - Combine musical knowledge with trading concepts
📊 EXPERIMENTAL USE:
• Creative alternative to traditional Fibonacci levels
• Educational exploration of mathematical harmony in markets
• Interesting way to visualize price ranges and retracements
• Novel approach for musicians interested in trading concepts
Important Note: This is an educational and experimental tool that applies musical theory concepts to price analysis. It should be used for learning and exploration purposes alongside proven technical analysis methods. The musical relationships are mathematically based but not validated as reliable trading signals.
Liquidity Sweep ReversalOverview
The Liquidity Sweep Reversal indicator is a sophisticated intraday trading tool designed to identify high-probability reversal opportunities after liquidity sweeps occur at key market levels. Based on Smart Money Concepts (SMC) and Institutional Order Flow analysis, this indicator helps traders catch market reversals when stop-loss clusters are hunted.
Key Features
🎯 Multi-Level Liquidity Analysis
Previous Day High/Low (PDH/PDL) detection
Previous Week High/Low (PWH/PWL) tracking
Session highs/lows for Asian, London, and New York markets
Real-time level validation and usage tracking
⚡ Advanced Signal Generation
CISD (Change In State of Delivery) detection algorithm
Engulfing pattern recognition at key levels
Liquidity sweep confirmation system
Directional bias filtering to avoid false signals
⏰ Kill Zone Integration
Pre-configured optimal trading windows
Asian Kill Zone (20:00-00:00 EST)
London Kill Zone (02:00-05:00 EST)
New York AM/PM Kill Zones (08:30-11:00 & 13:30-16:00 EST)
Optional kill zone-only trading mode
🛠 Customization Options
Multiple timezone support (NY, London, Tokyo, Shanghai, UTC)
Flexible HTF (Higher Time Frame) selection
Adjustable signal sensitivity
Visual customization for all levels and signals
Hide historical signals option for cleaner charts
How It Works
The indicator continuously monitors price action around key liquidity levels
When price sweeps liquidity (stop-loss hunting), it marks potential reversal zones
Confirmation signals are generated through CISD or engulfing patterns
Trade signals appear as arrows with color-coded candles for easy identification
Best Suited For
Intraday traders focusing on 1m to 15m timeframes
Smart Money Concepts (SMC) practitioners
Scalpers looking for high-probability reversal entries
Traders who understand liquidity and market structure
Usage Tips
Works best on liquid forex pairs and major indices
Combine with volume analysis for stronger confirmation
Use proper risk management - not all signals will be winners
Monitor higher timeframe bias for better accuracy
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日内流动性掠夺反向开单指标
指标简介
这是一款基于Smart Money概念（SMC）开发的高级日内交易指标，专门用于识别市场在关键价格水平扫除流动性后的反转机会。通过分析机构订单流和流动性分布，帮助交易者精准捕捉止损扫单后的市场反转点。
核心功能
多维度流动性分析
前日高低点（PDH/PDL）自动标记
前周高低点（PWH/PWL）动态跟踪
亚洲、伦敦、纽约三大交易时段高低点识别
关键位使用状态实时监控，避免重复信号
智能信号系统
CISD（Change In State of Delivery）算法检测
关键位吞没形态识别
流动性扫除确认机制
方向过滤系统，大幅降低虚假信号
黄金交易时段
内置Kill Zone时间窗口
支持亚洲、伦敦、纽约AM/PM四个黄金时段
可选择仅在Kill Zone内交易
时区智能切换，全球交易者适用
个性化设置
支持多时区切换（纽约/伦敦/东京/上海/UTC）
HTF周期自动适配或手动选择
信号灵敏度可调
所有图表元素均可自定义样式
历史信号隐藏功能，保持图表整洁
适用人群
日内短线交易者（1分钟-15分钟）
SMC交易体系践行者
追求高胜率反转入场的投机者
理解流动性和市场结构的专业交易者
使用建议
推荐用于主流加密货币、外汇对和股指期货
配合成交量分析效果更佳
严格止损，理性对待每个信号
关注更高时间框架的趋势方向
风险提示： 任何技术指标都不能保证100%准确，请结合自己的交易系统和风险管理使用。
Essa - Market Structure Crystal Ball SystemEssa - Market Structure Crystal Ball V2.0
Ever wished you had a glimpse into the market's next move? Stop guessing and start anticipating with the Market Structure Crystal Ball!
This isn't just another indicator that tells you what has happened. This is a comprehensive analysis tool that learns from historical price action to forecast the most probable future structure. It combines advanced pattern recognition with essential trading concepts to give you a unique analytical edge.
Key Features
The Predictive Engine (The Crystal Ball)
This is the core of the indicator. It doesn't just identify market structure; it predicts it.
Know the Odds: Get a real-time probability score (%) for the next structural point: Higher High (HH), Higher Low (HL), Lower Low (LL), or Lower High (LH).
Advanced Analysis: The engine considers the pattern sequence, the speed (velocity) of the move, and its size to find the most accurate historical matches.
Dynamic Learning: The indicator constantly updates its analysis as new price data comes in.
The All-in-One Dashboard
Your command center for at-a-glance information. No need to clutter your screen!
Market Phase: Instantly know if the market is in a "🚀 Strong Uptrend," "📉 Steady Downtrend," or "↔️ Consolidation."
Live Probabilities: See the updated forecasts for HH, HL, LL, and LH in a clean, easy-to-read format.
Confidence Level: The dashboard tells you how confident the algorithm is in its current prediction (Low, Medium, or High).
🎯 Dynamic Prediction Zones
Turn probabilities into actionable price areas.
Visual Targets: Based on the highest probability outcome, the indicator draws a target zone on your chart where the next structure point is likely to form.
Context-Aware: These zones are calculated using recent volatility and average swing sizes, making them adaptive to the current market conditions.
🔍 Fair Value Gap (FVG) Detector
Automatically identify and track key price imbalances.
Price Magnets: FVGs are automatically detected and drawn, acting as potential targets for price.
Smart Tracking: The indicator tracks the status of each FVG (Fresh, Partially Filled, or Filled) and uses this data to refine its predictions.
🌍 Trading Session Analysis
Never lose track of key session levels again.
Visualize Sessions: See the Asia, London, and New York sessions highlighted with colored backgrounds.
Key Levels: Automatically plots the high and low of each session, which are often critical support and resistance levels.
Breakout Alerts: Get notified when price breaks a session high or low.
📈 Multi-Timeframe (MTF) Context
Understand the bigger picture by integrating higher timeframe analysis directly onto your chart.
BOS & MSS: Automatically identifies Breaks of Structure (trend continuation) and Market Structure Shifts (potential reversals) from up to two higher timeframes.
Trade with the Trend: Align your intraday trades with the dominant trend for higher probability setups.
⚙️ How It Works in Simple Terms
1️⃣ It Learns: The indicator first identifies all the past swing points (HH, HL, LL, LH) and analyzes their characteristics (speed, size, etc.).
2️⃣ It Finds a Match: It looks at the most recent price action and searches through hundreds of historical bars to find moments that were almost identical.
3️⃣ It Analyzes the Outcome: It checks what happened next in those similar historical scenarios.
4️⃣ It Predicts: Based on that historical data, it calculates the probability of each potential outcome and presents it to you.
🚀 How to Use This Indicator in Your Trading
Confirmation Tool: Use a high probability score (e.g., >60% for a HH) to confirm your own bullish analysis before entering a trade.
Finding High-Probability Zones: Use the Prediction Zones as potential areas to take profit, or as reversal zones to watch for entries in the opposite direction.
Gauging Market Sentiment: Check the "Market Phase" on the dashboard. Avoid forcing trades when the indicator shows "😴 Low Volatility."
Confluence is Key: This indicator is incredibly powerful when combined with your existing strategy. Use it alongside supply/demand zones, moving averages, or RSI for ultimate confirmation.
We hope this tool gives you a powerful new perspective on the market. Dive into the settings to customize it to your liking!
If you find this indicator helpful, please give it a Boost 👍 and leave a comment with your feedback below! Happy trading!
Disclaimer: All predictions are probabilistic and based on historical data. Past performance is not indicative of future results. Always use proper risk management.
Reversal Point Dynamics⇋ Reversal Point Dynamics (RPD)
This is not an indicator; it is a complete system for deconstructing the mechanics of a market reversal. Reversal Point Dynamics (RPD) moves far beyond simplistic pattern recognition, venturing into a deep analysis of the underlying forces that cause trends to exhaust, pause, and turn. It is engineered from the ground up to identify high-probability reversal points by quantifying the confluence of market dynamics in real-time.
Where other tools provide a static signal, RPD delivers a dynamic probability. It understands that a true market turning point is not a single event, but a cascade of failing momentum, structural breakdown, and a shift in market order. RPD's core engine meticulously analyzes each of these dynamic components—the market's underlying state, its velocity and acceleration, its degree of chaos (entropy), and its structural framework. These forces are synthesized into a single, unified Probability Score, offering you an unprecedented, transparent view into the conviction behind every potential reversal.
This is not a "black box" system. It is an open-architecture engine designed to empower the discerning trader. Featuring real-time signal projection, an integrated Fibonacci R2R Target Engine, and a comprehensive dashboard that acts as your Dynamics Control Center , RPD gives you a complete, holistic view of the market's state.
The Theoretical Core: Deconstructing Market Dynamics
RPD's analytical power is born from the intelligent synthesis of multiple, distinct theoretical models. Each pillar of the engine analyzes a different facet of market behavior. The convergence of these analyses—the "Singularity" event referenced in the dashboard—is what generates the final, high-conviction probability score.
1. Pillar One: Quantum State Analysis (QSA)
This is the foundational analysis of the market's current state within its recent context. Instead of treating price as a random walk, QSA quantizes it into a finite number of discrete "states."
Formulaic Concept: The engine establishes a price range using the highest high and lowest low over the Adaptive Analysis Period. This range is then divided into a user-defined number of Analysis Levels. The current price is mapped to one of these states (e.g., in a 9-level system, State 0 is the absolute low, and State 8 is the absolute high).
Analytical Edge: This acts as a powerful foundational filter. The engine will only begin searching for reversal signals when the market has reached a statistically stretched, extreme state (e.g., State 0 or 8). The Edge Sensitivity input allows you to control exactly how close to this extreme edge the price must be, ensuring you are trading from points of maximum potential exhaustion.
2. Pillar Two: Price State Roc (PSR) - The Dynamics of Momentum
This pillar analyzes the kinetic forces of the market: its velocity and acceleration. It understands that it’s not just where the price is, but how it got there that matters.
Formulaic Concept: The psr function calculates two derivatives of price.
Velocity: (price - price ). This measures the speed and direction of the current move.
Acceleration: (velocity - velocity ). This measures the rate of change in that speed. A negative acceleration (deceleration) during a strong rally is a critical pre-reversal warning, indicating momentum is fading even as price may be pushing higher.
Analytical Edge: The engine specifically hunts for exhaustion patterns where momentum is clearly decelerating as price reaches an extreme state. This is the mechanical signature of a weakening trend.
3. Pillar Three: Market Entropy Analysis - The Dynamics of Order & Chaos
This is RPD's chaos filter, a concept borrowed from information theory. Entropy measures the degree of randomness or disorder in the market's price action.
Formulaic Concept: The calculateEntropy function analyzes recent price changes. A market moving directionally and smoothly has low entropy (high order). A market chopping back and forth without direction has high entropy (high chaos). The value is normalized between 0 and 1.
Analytical Edge: The most reliable trades occur in low-entropy, ordered environments. RPD uses the Entropy Threshold to disqualify signals that attempt to form in chaotic, unpredictable conditions, providing a powerful shield against whipsaw markets.
4. Pillar Four: The Synthesis Engine & Probability Calculation
This is where all the dynamic forces converge. The final probability score is a weighted calculation that heavily rewards confluence.
Formulaic Concept: The calculateProbability function intelligently assembles the final score:
A Base Score is established from trend strength and entropy.
An Entropy Score adds points for low entropy (order) and subtracts for high entropy (chaos).
A significant Divergence Bonus is awarded for a classic momentum divergence.
RSI & Volume Bonuses are added if momentum oscillators are in extreme territory or a volume spike confirms institutional interest.
MTF & Adaptive Bonuses add further weight for alignment with higher timeframe structure.
Analytical Edge: A signal backed by multiple dynamic forces (e.g., extreme state + decelerating momentum + low entropy + volume spike) will receive an exponentially higher probability score. This is the very essence of analyzing reversal point dynamics.
The Command Center: Mastering the Inputs
Every input is a precise lever of control, allowing you to fine-tune the RPD engine to your exact trading style, market, and timeframe.
🧠 Core Algorithm
Predictive Mode (Early Detection):
What It Is: Enables the engine to search for potential reversals on the current, unclosed bar.
How It Works: Analyzes intra-bar acceleration and state to identify developing exhaustion. These signals are marked with a ' ? ' and are tentative.
How To Use It: Enable for scalping or very aggressive day trading to get the earliest possible indication. Disable for swing trading or a more conservative approach that waits for full bar confirmation.
Live Signal Mode (Current Bar):
What It Is: A highly aggressive mode that plots tentative signals with a ' ! ' on the live bar based on projected price and momentum. These signals repaint intra-bar.
How It Works: Uses a linear regression projection of the close to anticipate a reversal.
How To Use It: For advanced users who use intra-bar dynamics for execution and understand the nature of repainting signals.
Adaptive Analysis Period:
What It Is: The main lookback period for the QSA, PSR, and Entropy calculations. This is the engine's "memory."
How It Works: A shorter period makes the engine highly sensitive to local price swings. A longer period makes it focus only on major, significant market structure.
How To Use It: Scalping (1-5m): 15-25. Day Trading (15m-1H): 25-40. Swing Trading (4H+): 40-60.
Fractal Strength (Bars):
What It Is: Defines the strength of the pivot detection used for confirming reversal events.
How It Works: A value of '2' requires a candle's high/low to be more extreme than the two bars to its left and right.
How To Use It: '2' is a robust standard. Increase to '3' for an even stricter definition of a structural pivot, which will result in fewer signals.
MTF Multiplier:
What It Is: Integrates pivot data from a higher timeframe for confluence.
How It Works: A multiplier of '4' on a 15-minute chart will pull pivot data from the 1-hour chart (15 * 4 = 60m).
How To Use It: Set to a multiple that corresponds to your preferred higher timeframe for contextual analysis.
🎯 Signal Settings
Min Probability %:
What It Is: Your master quality filter. A signal is only plotted if its score exceeds this threshold.
How It Works: Directly filters the output of the final probability calculation.
How To Use It: High-Quality (80-95): For A+ setups only. Balanced (65-75): For day trading. Aggressive (50-60): For scalping.
Min Signal Distance (Bars):
What It Is: A noise filter that prevents signals from clustering in choppy conditions.
How It Works: Enforces a "cooldown" period of N bars after a signal.
How To Use It: Increase in ranging markets to focus on major swings. Decrease on lower timeframes.
Entropy Threshold:
What It Is: Your "chaos shield." Sets the maximum allowable market randomness for a signal.
How It Works: If calculated entropy is above this value, the signal is invalidated.
How To Use It: Lower values (0.1-0.5): Extremely strict. Higher values (0.7-1.0): More lenient. 0.85 is a good balance.
Adaptive Entropy & Aggressive Mode:
What It Is: Toggles for dynamically adjusting the engine's core parameters.
How It Works: Adaptive Entropy can slightly lower the required probability in strong trends. Aggressive Mode uses more lenient settings across the board.
How To Use It: Keep Adaptive on. Use Aggressive Mode sparingly, primarily for scalping highly volatile assets.
📊 State Analysis
Analysis Levels:
What It Is: The number of discrete "states" for the QSA.
How It Works: More levels create a finer-grained analysis of price location.
How To Use It: 6-7 levels are ideal. Increasing to 9 can provide more precision on very volatile assets.
Edge Sensitivity:
What It Is: Defines how close to the absolute top/bottom of the range price must be.
How It Works: '0' means price must be in the absolute highest/lowest state. '3' allows a signal within the top/bottom 3 states.
How To Use It: '3' provides a good balance. Lower it to '1' or '0' if you only want to trade extreme exhaustion.
The Dashboard: Your Dynamics Control Center
The dashboard provides a transparent, real-time view into the engine's brain. Use it to understand the context behind every signal and to gauge the current market environment at a glance.
🎯 UNIFIED PROB SCORE
TOTAL SCORE: The highest probability score (either Peak or Valley) the engine is currently calculating. This is your main at-a-glance conviction metric. The "Singularity" header refers to the event where market dynamics align—the event RPD is built to detect.
Quality: A human-readable interpretation of the Total Score. "EXCEPTIONAL" (🌟) is a rare, A+ confluence event. "STRONG" (💪) is a high-quality, tradable setup.
📊 ORDER FLOW & COMPONENT ANALYSIS
Volume Spike: Shows if the current volume is significantly higher than average (YES/NO). A 'YES' adds major confirmation.
Peak/Valley Conf: This breaks down the probability score into its directional components, showing you the separate confidence levels for a potential top (Peak) versus a bottom (Valley).
🌌 MARKET STRUCTURE
HTF Trend: Shows the direction of the underlying trend based on a Supertrend calculation.
Entropy: The current market chaos reading. "🔥 LOW" is an ideal, ordered state for trading. "😴 HIGH" is a warning of choppy, unpredictable conditions.
🔮 FIB & R2R ZONE (Large Dashboard)
This section gives you the status of the Fibonacci Target Engine. It shows if an Active Channel (entry zone) or Stop Zone (invalidation zone) is active and displays the precise price levels for the static entry, target, and stop calculated at the time of the signal.
🛡️ FILTERS & PREDICTIVES (Large Dashboard)
This panel provides a status check on all the bonus filters. It shows the current RSI Status, whether a Divergence is present, and if a Live Pending signal is forming.
The Visual Interface: A Symphony of Data
Every visual element is designed for instant, intuitive interpretation of market dynamics.
Signal Markers: These are the primary outputs of the engine.
▼/▲ b: A fully confirmed signal that has passed all filters.
? b: A tentative signal generated in Predictive Mode, indicating developing dynamics.
◈ b: This diamond icon replaces the standard triangle when the signal is confirmed by a strong momentum divergence, highlighting it as a superior setup where dynamics are misaligned with price.
Harmonic Wave: The flowing, colored wave around the price.
What It Represents: The market's "flow dynamic" and volatility.
How to Interpret It: Expanding waves show increasing volatility. The color is tied to the "Quantum Color" in your theme, representing the underlying energy field of the market.
Entropy Particles: The small dots appearing above/below price.
What They Represent: A direct visualization of the "order dynamic."
How to Interpret Them: Their presence signifies a low-entropy, ordered state ideal for trading. Their color indicates the direction of momentum (PSR velocity). Their absence means the market is too chaotic (high entropy).
The Fibonacci Target Engine: The dynamic R2R system appearing post-signal.
Static Fib Levels: Colored horizontal lines representing the market's "structural dynamic."
The Green "Active Channel" Box: Your zone of consideration. An area to manage a potential entry.
Development Philosophy
Reversal Point Dynamics was engineered to answer a fundamental question: can we objectively measure the forces behind a market turn? It is a synthesis of concepts from market microstructure, statistics, and information theory. The objective was never to create a "perfect" system, but to build a robust decision-support tool that provides a measurable, statistical edge by focusing on the principle of confluence.
By demanding that multiple, independent market dynamics align simultaneously, RPD filters out the vast majority of market noise. It is designed for the trader who thinks in terms of probability and risk management, not in terms of certainties. It is a tool to help you discount the obvious and bet on the unexpected alignment of market forces.
"Markets are constantly in a state of uncertainty and flux and money is made by discounting the obvious and betting on the unexpected."
— George Soros
Trade with insight. Trade with anticipation.
— Dskyz, for DAFE Trading Systems
Active PMI Support/Resistance Levels [EdgeTerminal]The PMI Support & Resistance indicator revolutionizes traditional technical analysis by using Pointwise Mutual Information (PMI) - a statistical measure from information theory - to objectively identify support and resistance levels. Unlike conventional methods that rely on visual pattern recognition, this indicator provides mathematically rigorous, quantifiable evidence of price levels where significant market activity occurs.
- The Mathematical Foundation: Pointwise Mutual Information
Pointwise Mutual Information measures how much more likely two events are to occur together compared to if they were statistically independent. In our context:
Event A: Volume spikes occurring (high trading activity)
Event B: Price being at specific levels
The PMI formula calculates: PMI = log(P(A,B) / (P(A) × P(B)))
Where:
P(A,B) = Probability of volume spikes occurring at specific price levels
P(A) = Probability of volume spikes occurring anywhere
P(B) = Probability of price being at specific levels
High PMI scores indicate that volume spikes and certain price levels co-occur much more frequently than random chance would predict, revealing genuine support and resistance zones.
- Why PMI Outperforms Traditional Methods
Subjective interpretation: What one trader sees as significant, another might ignore
Confirmation bias: Tendency to see patterns that confirm existing beliefs
Inconsistent criteria: No standardized definition of "significant" volume or price action
Static analysis: Doesn't adapt to changing market conditions
No strength measurement: Can't quantify how "strong" a level truly is
PMI Advantages:
✅ Objective & Quantifiable: Mathematical proof of significance, not visual guesswork
✅ Statistical Rigor: Levels backed by information theory and probability
✅ Strength Scoring: PMI scores rank levels by statistical significance
✅ Adaptive: Automatically adjusts to different market volatility regimes
✅ Eliminates Bias: Computer-calculated, removing human interpretation errors
✅ Market Structure Aware: Reveals the underlying order flow concentrations
- How It Works
Data Processing Pipeline:
Volume Analysis: Identifies volume spikes using configurable thresholds
Price Binning: Divides price range into discrete levels for analysis
Co-occurrence Calculation: Measures how often volume spikes happen at each price level
PMI Computation: Calculates statistical significance for each price level
Level Filtering: Shows only levels exceeding minimum PMI thresholds
Dynamic Updates: Refreshes levels periodically while maintaining historical traces
Visual System:
Current Levels: Bright, thick lines with PMI scores - your actionable levels
Historical Traces: Faded previous levels showing market structure evolution
Strength Tiers: Line styles indicate PMI strength (solid/dashed/dotted)
Color Coding: Green for support, red for resistance
Info Table: Real-time display of strongest levels with scores
- Indicator Settings:
Core Parameters
Lookback Period (Default: 200)
Lower (50-100): More responsive to recent price action, catches short-term levels
Higher (300-500): Focuses on major historical levels, more stable but less responsive
Best for: Day trading (100-150), Swing trading (200-300), Position trading (400-500)
Volume Spike Threshold (Default: 1.5)
Lower (1.2-1.4): More sensitive, catches smaller volume increases, more levels detected
Higher (2.0-3.0): Only major volume surges count, fewer but stronger signals
Market dependent: High-volume stocks may need higher thresholds (2.0+), low-volume stocks lower (1.2-1.3)
Price Bins (Default: 50)
Lower (20-30): Broader price zones, less precise but captures wider areas
Higher (70-100): More granular levels, precise but may be overly specific
Volatility dependent: High volatility assets benefit from more bins (70+)
Minimum PMI Score (Default: 0.5)
Lower (0.2-0.4): Shows more levels including weaker ones, comprehensive view
Higher (1.0-2.0): Only statistically strong levels, cleaner chart
Progressive filtering: Start with 0.5, increase if too cluttered
Max Levels to Show (Default: 8)
Fewer (3-5): Clean chart focusing on strongest levels only
More (10-15): Comprehensive view but may clutter chart
Strategy dependent: Scalpers prefer fewer (3-5), swing traders more (8-12)
Historical Tracking Settings
Update Frequency (Default: 20 bars)
Lower (5-10): More frequent updates, captures rapid market changes
Higher (50-100): Less frequent updates, focuses on major structural shifts
Timeframe scaling: 1-minute charts need lower frequency (5-10), daily charts higher (50+)
Show Historical Levels (Default: True)
Enables the "breadcrumb trail" effect showing evolution of support/resistance
Disable for cleaner charts focusing only on current levels
Max Historical Marks (Default: 50)
Lower (20-30): Less memory usage, shorter history
Higher (100-200): Longer historical context but more resource intensive
Fade Strength (Default: 0.8)
Lower (0.5-0.6): Historical levels more visible
Higher (0.9-0.95): Historical levels very subtle
Visual Settings
Support/Resistance Colors: Choose colors that contrast well with your chart theme Line Width: Thicker lines (3-4) for better visibility on busy charts Show PMI Scores: Toggle labels showing statistical strength Label Size: Adjust based on screen resolution and chart zoom level
- Most Effective Usage Strategies
For Day Trading:
Setup: Lookback 100-150, Volume Threshold 1.8-2.2, Update Frequency 10-15
Use PMI levels as bounce/rejection points for scalp entries
Higher PMI scores (>1.5) offer better probability setups
Watch for volume spike confirmations at levels
For Swing Trading:
Setup: Lookback 200-300, Volume Threshold 1.5-2.0, Update Frequency 20-30
Enter on pullbacks to high PMI support levels
Target next resistance level with PMI score >1.0
Hold through minor levels, exit at major PMI levels
For Position Trading:
Setup: Lookback 400-500, Volume Threshold 2.0+, Update Frequency 50+
Focus on PMI scores >2.0 for major structural levels
Use for portfolio entry/exit decisions
Combine with fundamental analysis for timing
- Trading Applications:
Entry Strategies:
PMI Bounce Trades
Price approaches high PMI support level (>1.0)
Wait for volume spike confirmation (orange triangles)
Enter long on bullish price action at the level
Stop loss just below the PMI level
Target: Next PMI resistance level
PMI Breakout Trades
Price consolidates near high PMI level
Volume increases (watch for orange triangles)
Enter on decisive break with volume
Previous resistance becomes new support
Target: Next major PMI level
PMI Rejection Trades
Price approaches PMI resistance with momentum
Watch for rejection signals and volume spikes
Enter short on failure to break through
Stop above the PMI level
Target: Next PMI support level
Risk Management:
Stop Loss Placement
Place stops 0.1-0.5% beyond PMI levels (adjust for volatility)
Higher PMI scores warrant tighter stops
Use ATR-based stops for volatile assets
Position Sizing
Larger positions at PMI levels >2.0 (highest conviction)
Smaller positions at PMI levels 0.5-1.0 (lower conviction)
Scale out at multiple PMI targets
- Key Warning Signs & What to Watch For
Red Flags:
🚨 Very Low PMI Scores (<0.3): Weak statistical significance, avoid trading
🚨 No Volume Confirmation: PMI level without recent volume spikes may be stale
🚨 Overcrowded Levels: Too many levels close together suggests poor parameter tuning
🚨 Outdated Levels: Historical traces are reference only, not tradeable
Optimization Tips:
✅ Regular Recalibration: Adjust parameters monthly based on market regime changes
✅ Volume Context: Always check for recent volume activity at PMI levels
✅ Multiple Timeframes: Confirm PMI levels across different timeframes
✅ Market Conditions: Higher thresholds during high volatility periods
Interpreting PMI Scores
PMI Score Ranges:
0.5-1.0: Moderate statistical significance, proceed with caution
1.0-1.5: Good significance, reliable for most trading strategies
1.5-2.0: Strong significance, high-confidence trade setups
2.0+: Very strong significance, institutional-grade levels
Historical Context: The historical trace system shows how support and resistance evolve over time. When current levels align with multiple historical traces, it indicates persistent market memory at those prices, significantly increasing the level's reliability.
Weekly Volume USDT## Description
This Pine Script indicator displays the trading volume for each day of the current week (Monday through Sunday) in a clean table format on your TradingView chart. The volume is calculated in USDT equivalent and displayed in the top-right corner of the chart.
## Features
- **Weekly Volume Breakdown**: Shows individual daily volumes from Monday to Sunday
- **USDT Conversion**: Automatically converts volume to USDT using the average price (open + close / 2)
- **Smart Formatting**:
- Large numbers are formatted with K (thousands) and M (millions) suffixes
- Example: 1,234,567 → 1.23M USDT
- **Clean Table Display**: Fixed position table in the top-right corner
- **Current Week Focus**: Displays volumes for the current week only
- **Future Days Handling**: Days that haven't occurred yet in the current week show as "-"
## How It Works
1. The indicator calculates the average price for each day using (Open + Close) / 2
2. Multiplies the daily volume by the average price to get USDT-equivalent volume
3. Displays the results in an easy-to-read table format
## Use Cases
- **Volume Analysis**: Quickly identify which days of the week have the highest trading activity
- **Pattern Recognition**: Spot weekly volume patterns and trends
- **Trading Decisions**: Use volume information to inform your trading strategies
- **Market Activity Monitoring**: Keep track of market participation throughout the week
## Installation
Simply add this indicator to your TradingView chart and it will automatically display the weekly volume table in the top-right corner.
## Tags
#volume #weekly #USDT #table #analysis #trading #cryptocurrency
