VPSA-VTDDear Sir/Madam,
I am pleased to present the next iteration of my indicator concept, which, in my opinion, serves as a highly useful tool for analyzing markets using the Volume Spread Analysis (VSA) method or the Wyckoff methodology.
The VPSA (Volume-Price Spread Analysis), the latest version in the family of scripts I’ve developed, appears to perform its task effectively. The combination of visualizing normalized data alongside their significance, achieved through the application of Z-Score standardization, proved to be a sound solution. Therefore, I decided to take it a step further and expand my project with a complementary approach to the existing one.
Theory
At the outset, I want to acknowledge that I’m aware of the existence of other probabilistic models used in financial markets, which may describe these phenomena more accurately. However, in line with Occam's Razor, I aimed to maintain simplicity in the analysis and interpretation of the concepts below. For this reason, I focused on describing the data using the Gaussian distribution.
The data I read from the chart — primarily the closing price, the high-low price difference (spread), and volume — exhibit cyclical patterns. These cycles are described by Wyckoff's methodology, while VSA complements and presents them from a different perspective. I will refrain from explaining these methods in depth due to their complexity and broad scope. What matters is that within these cycles, various events occur, described by candles or bars in distinct ways, characterized by different spreads and volumes. When observing the chart, I notice periods of lower volatility, often accompanied by lower volumes, as well as periods of high volatility and significant volumes. It’s important to find harmony within this apparent chaos. I think that chart interpretation cannot happen without considering the broader context, but the more variables I include in the analytical process, the more challenges arise. For instance, how can I determine if something is large (wide) or small (narrow)? For elements like volume or spread, my script provides a partial answer to this question. Now, let’s get to the point.
Technical Overview
The first technique I applied is Min-Max Normalization. With its help, the script adjusts volume and spread values to a range between 0 and 1. This allows for a comparable bar chart, where a wide bar represents volume, and a narrow one represents spread. Without normalization, visually comparing values that differ by several orders of magnitude would be inconvenient. If the indicator shows that one bar has a unit spread value while another has half that value, it means the first bar is twice as large. The ratio is preserved.
The second technique I used is Z-Score Standardization. This concept is based on the normal distribution, characterized by variables such as the mean and standard deviation, which measures data dispersion around the mean. The Z-Score indicates how many standard deviations a given value deviates from the population mean. The higher the Z-Score, the more the examined object deviates from the mean. If an object has a Z-Score of 3, it falls within 0.1% of the population, making it a rare occurrence or even an anomaly. In the context of chart analysis, such strong deviations are events like climaxes, which often signal the end of a trend, though not always. In my script, I assigned specific colors to frequently occurring Z-Score values:
Below 1 – Blue
Above 1 – Green
Above 2 – Red
Above 3 – Fuchsia
These colors are applied to both spread and volume, allowing for quick visual interpretation of data.
Volume Trend Detector (VTD)
The above forms the foundation of VPSA. However, I have extended the script with a Volume Trend Detector (VTD). The idea is that when I consider market structure - by market structure, I mean the overall chart, support and resistance levels, candles, and patterns typical of spread and volume analysis as well as Wyckoff patterns - I look for price ranges where there is a lack of supply, demand, or clues left behind by Smart Money or the market's enigmatic identity known as the Composite Man. This is essential because, as these clues and behaviors of market participants — expressed through the chart’s dynamics - reflect the actions, decisions, and emotions of all players. These behaviors can help interpret the bull-bear battle and estimate the probability of their next moves, which is one of the key factors for a trader relying on technical analysis to make a trade decision.
I enhanced the script with a Volume Trend Detector, which operates in two modes:
Step-by-Step Logic
The detector identifies expected volume dynamics. For instance, when looking for signs of a lack of bullish interest, I focus on setups with decreasing volatility and volume, particularly for bullish candles. These setups are referred to as No Demand patterns, according to Tom Williams' methodology.
Simple Moving Average (SMA)
The detector can also operate based on a simple moving average, helping to identify systematic trends in declining volume, indicating potential imbalances in market forces.
I’ve designed the program to allow the selection of candle types and volume characteristics to which the script will pay particular attention and notify me of specific market conditions.
Advantages and Disadvantages
Advantages:
Unified visualization of normalized spread and volume, saving time and improving efficiency.
The use of Z-Score as a consistent and repeatable relative mechanism for marking examined values.
The use of colors in visualization as a reference to Z-Score values.
The possibility to set up a continuous alert system that monitors the market in real time.
The use of EMA (Exponential Moving Average) as a moving average for Z-Score.
The goal of these features is to save my time, which is the only truly invaluable resource.
Disadvantages:
The assumption that the data follows a normal distribution, which may lead to inaccurate interpretations.
A fixed analysis period, which may not be perfectly suited to changing market conditions.
The use of EMA as a moving average for Z-Score, listed both as an advantage and a disadvantage depending on market context.
I have included comments within the code to explain the logic behind each part. For those who seek detailed mathematical formulas, I invite you to explore the code itself.
Defining Program Parameters:
Numerical Conditions:
VPSA Period for Analysis – The number of candles analyzed.
Normalized Spread Alert Threshold – The expected normalized spread value; defines how large or small the spread should be, with a range of 0-1.00.
Normalized Volume Alert Threshold – The expected normalized volume value; defines how large or small the volume should be, with a range of 0-1.00.
Spread Z-SCORE Alert Threshold – The Z-SCORE value for the spread; determines how much the spread deviates from the average, with a range of 0-4 (a higher value can be entered, but from a logical standpoint, exceeding 4 is unnecessary).
Volume Z-SCORE Alert Threshold – The Z-SCORE value for volume; determines how much the volume deviates from the average, with a range of 0-4 (the same logical note as above applies).
Logical Conditions:
Logical conditions describe whether the expected value should be less than or equal to or greater than or equal to the numerical condition.
All four parameters accept two possibilities and are analogous to the numerical conditions.
Volume Trend Detector:
Volume Trend Detector Period for Analysis – The analysis period, indicating the number of candles examined.
Method of Trend Determination – The method used to determine the trend. Possible values: Step by Step or SMA.
Trend Direction – The expected trend direction. Possible values: Upward or Downward.
Candle Type – The type of candle taken into account. Possible values: Bullish, Bearish, or Any.
The last available setting is the option to enable a joint alert for VPSA and VTD.
When enabled, VPSA will trigger on the last closed candle, regardless of the VTD analysis period.
Example Use Cases (Labels Visible in the Script Window Indicate Triggered Alerts):
The provided labels in the chart window mark where specific conditions were met and alerts were triggered.
Summary and Reflections
The program I present is a strong tool in the ongoing "game" with the Composite Man.
However, it requires familiarity and understanding of the underlying methodologies to fully utilize its potential.
Of course, like any technical analysis tool, it is not without flaws. There is no indicator that serves as a perfect Grail, accurately signaling Buy or Sell in every case.
I would like to thank those who have read through my thoughts to the end and are willing to take a closer look at my work by using this script.
If you encounter any errors or have suggestions for improvement, please feel free to contact me.
I wish you good health and accurately interpreted market structures, leading to successful trades!
CatTheTrader
Cari dalam skrip untuk "market structure"
Volumetric Rejection Blocks [UAlgo]The Volumetric Rejection Blocks is designed to help traders identify and visualize key price levels where volumetric rejections occur, which may indicate a shift in market sentiment. These rejections can signal potential trend reversals or areas where price action is likely to face support or resistance. By drawing rejection blocks based on volumetric strength, the indicator allows users to observe where significant buying or selling pressure has been exerted, which can be used as a reference point for future price action.
Also indicator dynamically calculates swing highs and lows, analyzes bullish and bearish strengths based on volume-weighted price movements, and displays rejection blocks on the chart. Each rejection block represents an area where the price attempted to move beyond a certain level but faced rejection, either on a close or wick basis. This can be particularly useful for traders who rely on market structure and order flow to make informed decisions about entering or exiting trades.
🔶 Key Features
Swing Length Customization: Allows users to define the swing length, helping tailor the sensitivity of the swing high and low detection to the specific market conditions.
Rejection Block Visualization: Displays up to the last 10 rejection blocks based on user settings, clearly marking areas of significant bullish or bearish rejections.
Volumetric Strength Analysis: The indicator calculates bullish and bearish strength for each rejection block, based on volume-weighted price movements over the last few bars, giving insight into the intensity of the rejection.
Violation Check Type: Offers two options for violation detection—"Close" and "Wick". This allows traders to specify whether a price level is considered broken only if it closes beyond the level or if any wick breaches it.
Bullish and Bearish Block Coloring: Rejection blocks are colored to represent bullish (green) and bearish (red) rejection areas. The color transparency can be adjusted for clear visibility overlaid on the price chart.
Market Structure Labels: Labels and lines marking "Market Structure Shift" (MSS) and "Break of Structure" (BOS) are displayed, giving traders context about significant market structure changes.
🔶 Interpreting the Indicator
Rejection Blocks: These colored blocks on the chart indicate areas where the price faced significant buying or selling pressure. A green block suggests a bullish rejection (support zone), where buyers absorbed the sell-off, potentially pushing the price upward. Conversely, a red block indicates a bearish rejection (resistance zone), where sellers overpowered buyers, potentially driving the price lower.
Strength Analysis: The width of the green and red sections within a rejection block represents the relative bullish and bearish strengths. A wider green section indicates stronger bullish support, while a wider red section suggests more robust bearish resistance. This helps traders gauge the likelihood of price holding or breaching these levels.
Market Structure Shift (MSS) and Break of Structure (BOS): The indicator automatically detects and labels significant changes in market structure. An "MSS" label indicates the first break, suggesting a potential shift in trend direction. A "BOS" label indicates a subsequent confirmation in trend direction, allowing traders to recognize potential trend continuations.
Violation Check: Traders can choose how to interpret breaks of these rejection blocks. Using the "Close" option provides a more conservative approach, requiring a close beyond the level for confirmation. The "Wick" option is more aggressive, treating any wick beyond the level as a break.
🔶 Disclaimer
Use with Caution: This indicator is provided for educational and informational purposes only and should not be considered as financial advice. Users should exercise caution and perform their own analysis before making trading decisions based on the indicator's signals.
Not Financial Advice: The information provided by this indicator does not constitute financial advice, and the creator (UAlgo) shall not be held responsible for any trading losses incurred as a result of using this indicator.
Backtesting Recommended: Traders are encouraged to backtest the indicator thoroughly on historical data before using it in live trading to assess its performance and suitability for their trading strategies.
Risk Management: Trading involves inherent risks, and users should implement proper risk management strategies, including but not limited to stop-loss orders and position sizing, to mitigate potential losses.
No Guarantees: The accuracy and reliability of the indicator's signals cannot be guaranteed, as they are based on historical price data and past performance may not be indicative of future results.
Pivot-based Swing Highs and LowsRelease Notes for Pivot-based Swing Highs and Lows Indicator with HH, HL, LH, LL and Labels
Version 1.0.0
Release Date: 29th Sept 2024
Overview:
This Pine Script version 5 indicator is designed to identify and display Swing Highs and Swing Lows based on pivot points. The indicator visually marks Higher Highs (HH), Lower Highs (LH), Higher Lows (HL), and Lower Lows (LL) on the chart. The release introduces an improved visual representation with dotted lines and colored labels for easy identification of market structure, using plotshape() and line.new().
Key Features:
1. Pivot-Based Swing Identification:
The indicator uses ta.pivothigh() and ta.pivotlow() to detect significant pivot points on the chart.
The length of the pivot can be adjusted through the pivot_length parameter, allowing users to customize the sensitivity of swing identification.
2. Swing Highs and Lows with Labels:
Higher High (HH) and Lower High (LH) points are marked with green downward triangles.
Higher Low (HL) and Lower Low (LL) points are marked with red upward triangles.
The plotshape() function is used to provide clear visual markers, making it easy to spot the changes in market structure.
3. Dotted Line Visuals:
Green Dotted Lines: Connect Higher Highs (HH) and Higher Lows (HL) to their corresponding previous swings.
Red Dotted Lines: Connect Lower Highs (LH) and Lower Lows (LL) to their corresponding previous swings.
The use of color-coded dotted lines ensures better visual understanding of the trend continuation or reversal patterns.
4. Customizable Input:
The user can adjust the pivot_length parameter to fine-tune the detection of pivot highs and lows according to different timeframes or trading strategies.
Usage:
Higher High (HH): Green downward triangle, indicating a new high compared to the previous pivot high.
Lower High (LH): Green downward triangle, indicating a lower high compared to the previous pivot high.
Higher Low (HL): Red upward triangle, indicating a higher low compared to the previous pivot low.
Lower Low (LL): Red upward triangle, indicating a new lower low compared to the previous pivot low.
Dotted Lines: Connect previous swing points, helping users visualize the trend and potential market structure changes.
Improvements:
Label Substitution: In place of label.new() (which might cause issues in some environments), the indicator now uses plotshape() to provide a reliable and visually effective solution for marking swings.
Streamlined Performance: The logic for determining higher highs, lower highs, higher lows, and lower lows has been optimized for smooth performance across multiple timeframes.
Known Limitations:
No Direct Text Labels: Due to the constraints of plotshape(), text labels like "HH", "LH", "HL", and "LL" are not directly displayed. Instead, color-coded shapes are used for easy identification.
How to Use:
Apply the script to your chart via the TradingView Pine Editor.
Customize the pivot_length to suit your trading style or the timeframe you are analyzing.
Monitor the chart for marked Higher Highs, Lower Highs, Higher Lows, and Lower Lows for potential trend continuation or reversal opportunities.
Use the dotted lines to trace the evolution of market structure.
Please share your comments, thoughts. Also please follow me for more scripts in future. Mean time Happy Trading :)
Enhanced BOS Strategy with SL/TP and EMA TableDescription:
The Enhanced BOS (Break of Structure) Strategy is an advanced open-source trading indicator designed to identify key market structure changes, integrated with dynamic Stop Loss (SL) and Take Profit (TP) levels, along with an informative EMA (Exponential Moving Average) table for added trend analysis.
Key Features:
Break of Structure (BOS) Detection:
The script detects bullish and bearish BOS by identifying pivot points using a custom pivot period. When the price crosses above or below these points, it signals a potential market trend reversal or continuation.
Dynamic SL/TP Levels:
Users can toggle static SL/TP settings, which automatically calculate levels based on user-defined points. These levels are visualized on the chart with dotted lines and labeled for clarity.
Volume Filters:
The strategy includes a volume condition filter to ensure that only trades within a specified volume range are considered. This helps in avoiding low-volume trades that might lead to false signals.
EMA Table Display:
An on-chart table displaying the current values of the 13-period, 50-period, and 200-period EMAs. This provides a quick reference for trend identification and confirmation, helping traders to stay aligned with the broader market trend.
How It Works:
The script utilizes a combination of moving averages and pivot points to identify potential breakouts or breakdowns in market structure. When a bullish BOS is detected, and the volume conditions are met, the strategy suggests a long position, marking potential SL/TP levels. Similarly, it suggests short positions for bearish BOS.
The EMA table serves as a visual aid, providing real-time updates of the EMA values, allowing traders to gauge the market’s directional bias quickly.
How to Use:
Setting Parameters:
Adjust the pivot period to fine-tune BOS detection according to your trading style and the asset’s volatility.
Configure the SL/TP settings based on your risk tolerance and target profit levels.
Interpreting Signals:
A “Buy” label on the chart indicates a bullish BOS with volume confirmation, signaling a potential long entry.
A “Sell” label indicates a bearish BOS with volume confirmation, signaling a potential short entry.
The EMA table aids in confirming these signals, where the position of the fast, mid, and slow EMAs can provide additional context to the trend’s strength and direction.
Volume Filtering:
Ensure your trades are filtered through the script’s volume condition, which allows for the exclusion of low-volume periods that might generate unreliable signals.
Unique Value:
Unlike many other BOS strategies, this script integrates volume conditions and a visual EMA table, providing a comprehensive toolkit for traders looking to capture market structure shifts while maintaining an eye on trend direction and trade execution precision.
Additional Information:
This script is designed for use on standard bar or candlestick charts for best results.
It is open-source and free to use, encouraging collaboration and improvement by the TradingView community.
By combining powerful trend-following EMAs with the precision of BOS detection and the safety of volume filtering, the Enhanced BOS Strategy offers a balanced approach to trading market structure changes.
HTF OverlayThe "HTF Overlay" indicator provides a fully customizable higher timeframe (HTF) candle overlay on your current chart, designed to enhance your analysis and trading strategies. This tool is particularly useful for traders utilizing ICT's AMD power of three strategies, focusing on key candle OHLC/OLHC expansions, or those who need a quick reference to a higher timeframe without switching charts.
Originality and Usefulness:
The "HTF Overlay" script stands out due to its seamless integration of HTF candles onto lower timeframe charts. It ensures the current developing candle is left untouched, preserving the clarity of ongoing market activity. This feature is crucial for traders who need to analyze market structure on a smaller timeframe within the context of a larger timeframe candle.
Functionality:
Dynamic HTF Candle Display:
The script overlays HTF candles, updating them in real-time as new HTF candles form. This allows traders to see historical price behavior and trends alongside the current price action.
Visual Customization:
Users can adjust various aspects of the HTF candles, including the number of candles displayed, body colors, wick colors, wick thickness, and transparency levels for both body and wick. This ensures the overlay fits seamlessly with any chart setup.
Real-time Updates:
The indicator updates dynamically, ensuring that the HTF candles remain relevant to the current market conditions without affecting the developing candle.
How It Works:
Data Retrieval: The script uses the request.security function to fetch HTF data, including open, high, low, close, time, and time close values.
Candle Overlay: It calculates the visual parameters for the HTF candles (body and wick positions, colors, and transparency) and overlays them on the chart.
Update Mechanism: The script differentiates between new and ongoing candles, updating the current candle in real-time without disrupting its development.
How to Use:
Setup:
Select the higher timeframe you want to overlay (e.g., 240 minutes for 4-hour candles).
Specify the number of HTF candles to display.
Customize the appearance of the HTF candles, including colors and transparency settings for both the body and wicks.
Interpretation:
Use the HTF overlay to validate trading decisions by analyzing price action from a broader perspective.
Identify key support and resistance levels, trend directions, and potential reversal points by comparing current price action with HTF structures.
Integration:
Combine this indicator with other tools your strategy may use for a more comprehensive analysis.
Use it in conjunction with the first and last candle highlight feature to quickly identify key reference points and enhance your trading strategy.
Conclusion:
The "HTF Overlay" indicator is a versatile and essential tool for traders who need to incorporate higher timeframe analysis into their trading strategies. Its customizable features and real-time updates provide a deeper insight into market dynamics, helping traders make more informed decisions. Whether used for trend confirmation, breakout identification, or support/resistance analysis, this indicator enhances your ability to navigate the markets effectively.
ICT Turtle Soup | Flux Charts💎 GENERAL OVERVIEW
Introducing our new ICT Turtle Soup Indicator! This indicator is built around the ICT "Turtle Soup" model. The strategy has 5 steps for execution which are described in this write-up. For more information about the process, check the "HOW DOES IT WORK" section.
Features of the new ICT Turtle Soup Indicator :
Implementation of ICT's Turtle Soup Strategy
Adaptive Entry Method
Customizable Execution Settings
Customizable Backtesting Dashboard
Alerts for Buy, Sell, TP & SL Signals
📌 HOW DOES IT WORK ?
The ICT Turtle Soup strategy may have different implementations depending on the selected method of the trader. This indicator's implementation is described as :
1. Mark higher timerame liquidity zones.
Liquidity zones are where a lot of market orders sit in the chart. They are usually formed from the long / short position holders' "liquidity" levels. There are various ways to find them, most common one being drawing them on the latest high & low pivot points in the chart, which this indicator does.
2. Mark current timeframe market structure.
The market structure is the current flow of the market. It tells you if the market is trending right now, and the way it's trending towards. It's formed from swing higs, swing lows and support / resistance levels.
3. Wait for market to make a liquidity grab on the higher timeframe liquidity zone.
A liquidity grab is when the marked liquidity zones have a false breakout, which means that it gets broken for a brief amount of time, but then price falls back to it's previous position.
4. Buyside liquidity grabs are "Short" entries and Sellside liquidity grabs are "Long" entries by default.
5. Wait for the market-structure shift in the current timeframe for entry confirmation.
A market-structure shift happens when the current market structure changes, usually when a new swing high / swing low is formed. This indicator uses it as a confirmation for position entry as it gives an insight of the new trend of the market.
6. Place Take-Profit and Stop-Loss levels according to the risk ratio.
This indicator uses "Average True Range" when placing the stop-loss & take-profit levels. Average True Range calculates the average size of a candle and the indicator places the stop-loss level using ATR times the risk setting determined by the user, then places the take-profit level trying to keep a minimum of 1:1 risk-reward ratio.
This indicator follows these steps and inform you step by step by plotting them in your chart.
🚩UNIQUENESS
This indicator is an all-in-one suit for the ICT's Turtle Soup concept. It's capable of plotting the strategy, giving signals, a backtesting dashboard and alerts feature. It's designed for simplyfing a rather complex strategy, helping you to execute it with clean signals. The backtesting dashboard allows you to see how your settings perform in the current ticker. You can also set up alerts to get informed when the strategy is executable for different tickers.
⚙️SETTINGS
1. General Configuration
MSS Swing Length -> The swing length when finding liquidity zones for market structure-shift detection.
Higher Timeframe -> The higher timeframe to look for liquidity grabs. This timeframe setting must be higher than the current chart's timeframe for the indicator to work.
Breakout Method -> If "Wick" is selected, a bar wick will be enough to confirm a market structure-shift. If "Close" is selected, the bar must close above / below the liquidity zone to confirm a market structure-shift.
Entry Method ->
"Classic" : Works as described on the "HOW DOES IT WORK" section.
"Adaptive" : When "Adaptive" is selected, the entry conditions may chance depending on the current performance of the indicator. It saves the entry conditions and the performance of the past entries, then for the new entries it checks if it predicted the liquidity grabs correctly with the current setup, if so, continues with the same logic. If not, it changes behaviour to reverse the entries from long / short to short / long.
2. TP / SL
TP / SL Method -> If "Fixed" is selected, you can adjust the TP / SL ratios from the settings below. If "Dynamic" is selected, the TP / SL zones will be auto-determined by the algorithm.
Risk -> The risk you're willing to take if "Dynamic" TP / SL Method is selected. Higher risk usually means a better winrate at the cost of losing more if the strategy fails. This setting is has a crucial effect on the performance of the indicator, as different tickers may have different volatility so the indicator may have increased performance when this setting is correctly adjusted.
D3m4h GIFVGDescription
D3m4h GIFVG is an indicator designed to automatically detect market imbalances—often referred to as FVGs (Fair Value Gaps)—and potential pivot-based shifts in market structure. It offers a dynamic approach to visualizing supply/demand inefficiencies and pivot-based trend changes. Key features include:
1. Pivot-Based Bullish/Bearish Detection
The indicator identifies higher-high/lower-low pivot logic as well as “outside bar” pivots.
It tracks when the market transitions from bullish to bearish ranges, or vice versa, by using multiple checks:
Pivot low/high detection
Break-of-structure (when price crosses the last pivot)
Opposing FVG detection to confirm an intraday pivot shift
2. FVG (Fair Value Gap) Detection
The script automatically scans for bullish or bearish FVG conditions:
Bullish FVG: Candle at position (bar_index - 2) has a high below the current candle’s low.
Bearish FVG: Candle at position (bar_index - 2) has a low above the current candle’s high.
When it detects an FVG, it draws a box on the chart to highlight the price gap (yellow boxes by default).
3. Pivot Range FVG
If an FVG forms while the market is in a bullish pivot range, the script can paint a special “blue” FVG to underscore its significance. The same logic applies if a newly formed FVG appears in a bearish pivot range.
4. Filled Gap Cleanup
You can optionally hide standard FVG boxes once they’re filled. For example, if the candle’s body (or candle range) covers that gap, the box is removed to keep your chart clean.
5. Pivot-Range FVG “Raided” Cleanup
If the pivot-based FVG is later filled from the opposing direction, it turns green and can optionally remove itself after a set number of bars.
6. Informative Table
A small table on the chart optionally displays whether or not the pivot-based FVG has been “raided”. You can toggle this table on/off in the settings.
How It Works
1. Pivot Shifts
The script tracks the last pivot high/low using a combination of candle-based pivot detection and break-of-structure checks (when price crosses the last pivot in the opposite direction).
When a shift is detected, the pivot range ID increments—this helps the script know when to remove old pivot-based FVGs or draw new ones.
2. FVG Formation
Each new bar checks if a bullish or bearish FVG formed (comparing the high of bar two bars ago to the current low, or the low of bar two bars ago to the current high).
If one is found, a box is drawn to highlight the imbalance. Its color and extension depend on script settings.
3. Imbalance or Pivot FVG
Standard imbalance boxes appear in yellow.
If the new imbalance coincides with a bullish or bearish pivot range, a special “pivot imbalance” box in blue is drawn.
3. Hide Filled
If a newly formed candle’s body fully covers the FVG, the box is considered filled. If Hide Filled Gaps is enabled, the box is deleted once it’s covered.
4. Raid Status
For the pivot-based (blue) FVG, once price invalidates it from the opposite side, it changes color to green and gets removed after a user-defined number of bars.
How to Use
1. Look for FVGs
Observe yellow boxes to identify potential intraday imbalances. Watch for price returning to fill these zones.
If you see a “blue” box, it signifies a pivot-based FVG in line with a recognized shift in structure—arguably a higher-probability zone.
2. “Hide Filled Gaps”
Turn this on if you only want to see currently active or partially filled imbalances. The script cleans up old, fully covered boxes to keep your chart neat.
3. Pivot Shifts
Note the script’s internal pivot logic. Each new pivot re-defines bullish or bearish states. Use these states to gauge the short-term trend shifts.
4. Toggle the Table
You can show or hide the chart table by enabling/disabling “Show Table” from the inputs. This table indicates if the pivot-based “GIFVG” has been “raided” or not.
5. Extend Count
Adjust the extendCount in the code if you want FVG boxes to extend further or shorter in time.
Underlying Concepts
Fair Value Gaps
Market inefficiencies that occur when price jumps, leaving a “gap” from the candle 2 bars ago to the current candle. They can act like mini supply/demand zones where price may revisit for balance.
Pivot Ranges
The script tries to maintain an internal sense of whether the market is in a bullish or bearish pivot range. When it sees a contrary FVG or break-of-structure, it flips the pivot state.
Outside Bars
A candle that has both a higher high and a lower low than the previous bar. The script uses these to mark significant pivot shifts.
By combining pivot-based logic with FVG detection, the D3m4h GIFVG indicator helps highlight potential areas of liquidity or unfilled value. Traders can use these zones to plan entries/exits or to confirm short-term trend shifts.
Vortex Sniper Elite @DaviddTechVortex Sniper Elite @DaviddTech
Vortex Sniper Elite @DaviddTech is a comprehensive trading system designed to deliver high-probability trade setups across all market conditions. By seamlessly integrating adaptive baseline detection, squeeze momentum analysis, and advanced vortex filtering, this indicator provides traders with a complete edge-based approach to market analysis.
🔥 Key Features:
Complete Model Integration:
Baseline: Advanced McGinley Dynamic indicator for superior trend detection
Confirmation #1: Enhanced TTM Squeeze for momentum and volatility analysis
Confirmation #2: Dual Tether Line system for dynamic market structure mapping
Volatility Filter: Specialized Vortex indicator for precision entry timing
Adaptive Stop Loss: Proprietary trailing stop system based on ATR calculations
Advanced Visual Dashboard:
Real-time component analysis with strength metrics
Color-coded signal status for immediate trade assessment
Squeeze state monitoring with visual confirmation
Vortex divergence strength percentage for optimal entries
Premium Signal Detection:
Multi-timeframe compatible system for scaling strategies
Automated buy/sell signals at optimal entry points
Clear exit signals for risk management
Squeeze momentum visualization for timing precision
DaviddTech Alpha Edge System:
Gradient transparency algorithm for visual trend strength confirmation
Bar coloring system based on momentum direction
Background highlighting for active signal states
Dashboard for ease of understanding
💰 Trading Applications:
Sniper Entries: Utilize the Vortex confirmation to pinpoint precise entry points
Trend Alignment: McGinley baseline establishes the primary market direction
Volatility Awareness: TTM Squeeze identifies optimal market conditions
Risk Management: Set stops based on the adaptive trailing stop system
Position Management: Monitor dashboard metrics for changing market conditions
Vortex Sniper Elite @DaviddTech represents the culmination of the DaviddTech methodology in one cohesive system. Whether you're a day trader seeking precise entries or a swing trader looking for significant market moves, this indicator delivers the structured approach needed to consistently extract profits from any market condition.
DaviddTech Trading System Explained:
The DaviddTech methodology follows a strict component-based approach:
The Baseline establishes the primary trend direction, acting as your first filter
Confirmation Indicators validate potential trade setups only when aligned with the baseline
The Volatility/Volume Indicator ensures you only enter trades with sufficient directional momentum
A Trailing Stop System provides mathematically optimized exit points
Vortex Sniper Elite integrates all these components into a visually intuitive system that eliminates guesswork and enforces disciplined trading decisions.
Recommended Settings:
This indicator comes pre-configured with optimized parameters, but feel free to adjust based on your timeframe:
For day trading: Reduce Baseline and TTM lengths by 30-40%
For swing trading: Consider increasing Tether and Trail Stop lengths by 25-50%
For scalping: Focus on Vortex confirmation with shorter timeframes
Best Practices:
Wait for all components to align before entering trades
Use the dashboard to evaluate the strength of each signal
Monitor squeeze states for potential volatility expansion
Let the trailing stop system handle your exits
Backtest across multiple timeframes to find your optimal settings
Quarterly Theory ICT 02 [TradingFinder] True Open Session 90 Min🔵 Introduction
The Quarterly Theory ICT indicator is an advanced analytical system built on ICT (Inner Circle Trader) concepts and fractal time. It divides time into four quarters (Q1, Q2, Q3, Q4), and is designed based on the consistent repetition of these phases across all trading timeframes (annual, monthly, weekly, daily, and even shorter trading sessions).
Each cycle consists of four distinct phases: the first phase (Q1) is the Accumulation phase, characterized by price consolidation; the second phase (Q2), known as Manipulation or Judas Swing, is marked by initial false movements indicating a potential shift; the third phase (Q3) is Distribution, where price volatility peaks; and the fourth phase (Q4) is Continuation/Reversal, determining whether the previous trend continues or reverses.
🔵 How to Use
The central concept of this strategy is the "True Open," which refers to the actual starting point of each time cycle. The True Open is typically defined at the beginning of the second phase (Q2) of each cycle. Prices trading above or below the True Open serve as a benchmark for predicting the market's potential direction and guiding trading decisions.
The practical application of the Quarterly Theory strategy relies on accurately identifying True Open points across various timeframes.
True Open points are defined as follows :
Yearly Cycle :
Q1: January, February, March
Q2: April, May, June (True Open: April Monthly Open)
Q3: July, August, September
Q4: October, November, December
Monthly Cycle :
Q1: First Monday of the month
Q2: Second Monday of the month (True Open: Daily Candle Open price on the second Monday)
Q3: Third Monday of the month
Q4: Fourth Monday of the month
Weekly Cycle :
Q1: Monday
Q2: Tuesday (True Open: Daily Candle Open Price on Tuesday)
Q3: Wednesday
Q4: Thursday
Daily Cycle :
Q1: 18:00 - 00:00 (Asian session)
Q2: 00:00 - 06:00 (True Open: Start of London Session)
Q3: 06:00 - 12:00 (NY AM)
Q4: 12:00 - 18:00 (NY PM)
90 Min Asian Session :
Q1: 18:00 - 19:30
Q2: 19:30 - 21:00 (True Open at 19:30)
Q3: 21:00 - 22:30
Q4: 22:30 - 00:00
90 Min London Session :
Q1: 00:00 - 01:30
Q2: 01:30 - 03:00 (True Open at 01:30)
Q3: 03:00 - 04:30
Q4: 04:30 - 06:00
90 Min New York AM Session :
Q1: 06:00 - 07:30
Q2: 07:30 - 09:00 (True Open at 07:30)
Q3: 09:00 - 10:30
Q4: 10:30 - 12:00
90 Min New York PM Session :
Q1: 12:00 - 13:30
Q2: 13:30 - 15:00 (True Open at 13:30)
Q3: 15:00 - 16:30
Q4: 16:30 - 18:00
Micro Cycle (22.5-Minute Quarters) : Each 90-minute quarter is further divided into four 22.5-minute sub-segments (Micro Sessions).
True Opens in these sessions are defined as follows :
Asian Micro Session :
True Session Open : 19:30 - 19:52:30
London Micro Session :
T rue Session Open : 01:30 - 01:52:30
New York AM Micro Session :
True Session Open : 07:30 - 07:52:30
New York PM Micro Session :
True Session Open : 13:30 - 13:52:30
By accurately identifying these True Open points across various timeframes, traders can effectively forecast the market direction, analyze price movements in detail, and optimize their trading positions. Prices trading above or below these key levels serve as critical benchmarks for determining market direction and making informed trading decisions.
🔵 Setting
Show True Range : Enable or disable the display of the True Range on the chart, including the option to customize the color.
Extend True Range Line : Choose how to extend the True Range line on the chart, with the following options:
None: No line extension
Right: Extend the line to the right
Left: Extend the line to the left
Both: Extend the line in both directions (left and right)
Show Table : Determines whether the table—which summarizes the phases (Q1 to Q4)—is displayed.
Show More Info : Adds additional details to the table, such as the name of the phase (Accumulation, Manipulation, Distribution, or Continuation/Reversal) or further specifics about each cycle.
🔵 Conclusion
The Quarterly Theory ICT, by dividing time into four distinct quarters (Q1, Q2, Q3, and Q4) and emphasizing the concept of the True Open, provides a structured and repeatable framework for analyzing price action across multiple time frames.
The consistent repetition of phases—Accumulation, Manipulation (Judas Swing), Distribution, and Continuation/Reversal—allows traders to effectively identify recurring price patterns and critical market turning points. Utilizing the True Open as a benchmark, traders can more accurately determine potential directional bias, optimize trade entries and exits, and manage risk effectively.
By incorporating principles of ICT (Inner Circle Trader) and fractal time, this strategy enhances market forecasting accuracy across annual, monthly, weekly, daily, and shorter trading sessions. This systematic approach helps traders gain deeper insight into market structure and confidently execute informed trading decisions.
[TehThomas] - ICT Volume ImbalanceThis script is a Volume Imbalance (VI) detector and visualizer for use on the TradingView platform. The goal of the script is to automatically identify areas where there are significant imbalances in the volume of trades between consecutive candlesticks and visually highlight these areas. These imbalances can provide traders with valuable insights about the market’s current condition, often signaling potential reversal or continuation points based on price and volume action.
ICT (Inner Circle Trader) Concept of Volume Imbalances
Volume imbalances are a critical concept in the ICT trading methodology. They refer to situations where there is an unusual or significant difference in volume between two consecutive candlesticks, which might indicate institutional or large player activity. According to ICT principles, these imbalances can show us areas of market inefficiency or potential price manipulation. By identifying these imbalances, traders can gain an edge in understanding where the market is likely to move next.
Bullish and Bearish Volume Imbalances:
Bullish Volume Imbalance: This occurs when there is a strong increase in buying pressure, typically indicated by a higher volume on a candle that closes significantly above the previous one, often leaving a gap or larger price movement. The market could be preparing to push higher, and the volume shows a clear shift in buying demand.
Bearish Volume Imbalance:
Conversely, a bearish imbalance occurs when there is a strong increase in selling pressure, typically signaled by a candle that closes significantly lower than the previous one, again with higher volume. This could indicate that large players are offloading positions, and the price is likely to drop further.
Key Features and Functions of the Script
The script automates the process of detecting these volume imbalances and visually marking them on a price chart. Let’s explore its functionality in detail.
1. Inputs Section
The script allows for significant customization through its input options, which help traders adjust the detection and visualization of volume imbalances based on their individual preferences and trading style. Below are the details:
lookback (250 bars): This input specifies the number of bars (or candles) the script should look back when analyzing the volume imbalance. By setting this to 250, the user is looking at the last 250 bars on the chart to detect any significant volume imbalances. This period is adjustable between 50 to 500 bars.
volumeThreshold (1.0 multiplier): This input helps set the sensitivity for identifying volume imbalances. The script compares the volume of the current candle with the previous one, and if the current volume exceeds the previous volume by this threshold multiplier (in this case, 1.0 means at least equal to the previous volume), then it triggers an imbalance. Users can adjust the multiplier to suit different market conditions.
showBoxes (true/false): This toggle determines whether the boxes representing volume imbalances are drawn on the chart. When enabled, the script visually highlights the imbalances with colored boxes.
fillBaseColor (orange with 80% opacity): This is the color setting for the background of the imbalance boxes. A softer color (like orange with opacity) ensures the imbalance is highlighted without obscuring the price action.
borderColor (gray): The color of the border around the imbalance boxes. This adds a visual distinction to make the imbalance areas more visible.
borderWidth (1 pixel): This controls the width of the box's border to adjust how prominent it appears.
rightOffset (30 bars): This input controls how far the imbalance box extends to the right on the chart. It helps users anticipate the potential continuation of the imbalance beyond the current candle.
allowWickOverlap (true/false): This setting allows imbalances to be identified even if the wicks of the two consecutive candlesticks overlap. If set to false, only imbalances where the bodies of the candlesticks don’t overlap are considered.
showBrokenBoxes (true/false): If enabled, once a volume imbalance no longer holds true (i.e., the price breaks through the box), the box is marked as "broken." If disabled, the box is deleted when the imbalance condition no longer applies.
brokenBoxColor (red): This controls the color of the box when it is broken, which can be used as a visual cue that the imbalance was invalidated or no longer valid for analysis.
2. Volume Imbalance Function
This is the core function of the script, where the logic to detect bullish and bearish volume imbalances is implemented.
Bullish Imbalance Condition:
The first condition checks if the low of the current candle is greater than the high of the previous candle. This suggests that the market is moving upward with buying pressure.
The second condition checks whether the volume of the current candle is higher than the previous candle by the volumeThreshold multiplier. If both conditions are satisfied, a bullish imbalance is detected.
Bearish Imbalance Condition:
The first condition checks if the high of the current candle is lower than the low of the previous candle. This suggests downward price action with selling pressure.
The second condition checks whether the current volume exceeds the previous volume by the threshold
Allow Wick Overlap: If allowWickOverlap is set to true, the script will still detect imbalances if the wicks of the two candles overlap (common in volatile markets). If false, imbalances are only considered if the wicks do not overlap.
3. Box Creation and Management
When a volume imbalance is detected, the script creates a box on the chart:
The bullish imbalance box is drawn using the minimum of the open and close of the current bar as the top boundary and the maximum of the open and close of the previous bar as the bottom boundary.
Conversely, the bearish imbalance box is drawn in reverse, using the maximum of the current bar’s open and close as the top boundary and the minimum of the previous bar’s open and close as the bottom boundary.
Once the box is created, it is displayed on the chart with the specified background color, border color, and width.
4. Processing Existing Boxes
After detecting a new imbalance and drawing a box, the script checks whether the box should still remain on the chart:
If the price moves beyond the boundaries of the imbalance box, the box is marked as broken (if showBrokenBoxes is enabled), and its color is changed to red, signifying that the imbalance is no longer valid.
If the box remains intact (i.e., the price has not broken the defined boundaries), the script keeps the box extended to the right as the market continues to evolve.
5. Removing Outdated Boxes
Lastly, the script removes boxes that are older than the specified lookback period. For example, if a box was created 250 bars ago, it will be deleted after that period. This ensures the chart stays clean and only focuses on relevant imbalances.
Why This Script is Useful for Traders
This script is extremely valuable for traders, especially those following the ICT methodology, because it automates the process of detecting market inefficiencies or imbalances that might signal future price action. Here’s why it’s particularly useful:
Identifying Key Areas of Interest: Volume imbalances often point to areas where institutional or large-scale traders have entered the market. These areas could provide clues about the next significant move in the market.
Visualizing Market Structure: By automatically drawing boxes around volume imbalances, the script helps traders visually identify potential areas of support, resistance, or turning points, enabling them to make informed trading decisions.
Time Efficiency: Instead of manually analyzing each candlestick and volume spike, this script does the heavy lifting, saving traders valuable time and allowing them to focus on other aspects of their strategy.
Enhanced Trade Entries and Exits: By understanding where volume imbalances are occurring, traders can time their entries (buying during bullish imbalances and selling during bearish ones) and exits (as imbalances break) more effectively, thus improving their chances of success.
Conclusion
In summary, this script is a powerful tool for traders looking to implement volume imbalance strategies based on the ICT methodology. It automates the identification and visualization of significant imbalances in price and volume, offering traders a clear visual representation of potential market turning points. By customizing the settings, traders can tailor the script to their preferred timeframes and sensitivity, making it a flexible and effective tool for any trading strategy.
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[3Commas] Turtle StrategyTurtle Strategy
🔷 What it does: This indicator implements a modernized version of the Turtle Trading Strategy, designed for trend-following and automated trading with webhook integration. It identifies breakout opportunities using Donchian channels, providing entry and exit signals.
Channel 1: Detects short-term breakouts using the highest highs and lowest lows over a set period (default 20).
Channel 2: Acts as a confirmation filter by applying an offset to the same period, reducing false signals.
Exit Channel: Functions as a dynamic stop-loss (wait for candle close), adjusting based on market structure (default 10 periods).
Additionally, traders can enable a fixed Take Profit level, ensuring a systematic approach to profit-taking.
🔷 Who is it for:
Trend Traders: Those looking to capture long-term market moves.
Bot Users: Traders seeking to automate entries and exits with bot integration.
Rule-Based Traders: Operators who prefer a structured, systematic trading approach.
🔷 How does it work: The strategy generates buy and sell signals using a dual-channel confirmation system.
Long Entry: A buy signal is generated when the close price crosses above the previous high of Channel 1 and is confirmed by Channel 2.
Short Entry: A sell signal occurs when the close price falls below the previous low of Channel 1, with confirmation from Channel 2.
Exit Management: The Exit Channel acts as a trailing stop, dynamically adjusting to price movements. To exit the trade, wait for a full bar close.
Optional Take Profit (%): Closes trades at a predefined %.
🔷 Why it’s unique:
Modern Adaptation: Updates the classic Turtle Trading Strategy, with the possibility of using a second channel with an offset to filter the signals.
Dynamic Risk Management: Utilizes a trailing Exit Channel to help protect gains as trades move favorably.
Bot Integration: Automates trade execution through direct JSON signal communication with your DCA Bots.
🔷 Considerations Before Using the Indicator:
Market & Timeframe: Best suited for trending markets; higher timeframes (e.g., H4, D1) are recommended to minimize noise.
Sideways Markets: In choppy conditions, breakouts may lead to false signals—consider using additional filters.
Backtesting & Demo Testing: It is crucial to thoroughly backtest the strategy and run it on a demo account before risking real capital.
Parameter Adjustments: Ensure that commissions, slippage, and position sizes are set accurately to reflect real trading conditions.
🔷 STRATEGY PROPERTIES
Symbol: BINANCE:ETHUSDT (Spot).
Timeframe: 4h.
Test Period: All historical data available.
Initial Capital: 10000 USDT.
Order Size per Trade: 1% of Capital, you can use a higher value e.g. 5%, be cautious that the Max Drawdown does not exceed 10%, as it would indicate a very risky trading approach.
Commission: Binance commission 0.1%, adjust according to the exchange being used, lower numbers will generate unrealistic results. By using low values e.g. 5%, it allows us to adapt over time and check the functioning of the strategy.
Slippage: 5 ticks, for pairs with low liquidity or very large orders, this number should be increased as the order may not be filled at the desired level.
Margin for Long and Short Positions: 100%.
Indicator Settings: Default Configuration.
Period Channel 1: 20.
Period Channel 2: 20.
Period Channel 2 Offset: 20.
Period Exit: 10.
Take Profit %: Disable.
Strategy: Long & Short.
🔷 STRATEGY RESULTS
⚠️Remember, past results do not guarantee future performance.
Net Profit: +516.87 USDT (+5.17%).
Max Drawdown: -100.28 USDT (-0.95%).
Total Closed Trades: 281.
Percent Profitable: 40.21%.
Profit Factor: 1.704.
Average Trade: +1.84 USDT (+1.80%).
Average # Bars in Trades: 29.
🔷 How to Use It:
🔸 Adjust Settings:
Select your asset and timeframe suited for trend trading.
Adjust the periods for Channel 1, Channel 2, and the Exit Channel to align with the asset’s historical behavior. You can visualize these channels by going to the Style tab and enabling them.
For example, if you set Channel 2 to 40 with an offset of 40, signals will take longer to appear but will aim for a more defined trend.
Experiment with different values, a possible exit configuration is using 20 as well. Compare the results and adjust accordingly.
Enable the Take Profit (%) option if needed.
🔸Results Review:
It is important to check the Max Drawdown. This value should ideally not exceed 10% of your capital. Consider adjusting the trade size to ensure this threshold is not surpassed.
Remember to include the correct values for commission and slippage according to the symbol and exchange where you are conducting the tests. Otherwise, the results will not be realistic.
If you are satisfied with the results, you may consider automating your trades. However, it is strongly recommended to use a small amount of capital or a demo account to test proper execution before committing real funds.
🔸Create alerts to trigger the DCA Bot:
Verify Messages: Ensure the message matches the one specified by the DCA Bot.
Multi-Pair Configuration: For multi-pair setups, enable the option to add the symbol in the correct format.
Signal Settings: Enable the option to receive long or short signals (Entry | TP | SL), copy and paste the messages for the DCA Bots configured.
Alert Setup:
When creating an alert, set the condition to the indicator and choose "alert() function call only".
Enter any desired Alert Name.
Open the Notifications tab, enable Webhook URL, and paste the Webhook URL.
For more details, refer to the section: "How to use TradingView Custom Signals".
Finalize Alerts: Click Create, you're done! Alerts will now be sent automatically in the correct format.
🔷 INDICATOR SETTINGS
Period Channel 1: Period of highs and lows to trigger signals
Period Channel 2: Period of highs and lows to filter signals
Offset: Move Channel 2 to the right x bars to try to filter out the favorable signals.
Period Exit: It is the period of the Donchian channel that is used as trailing for the exits.
Strategy: Order Type direction in which trades are executed.
Take Profit %: When activated, the entered value will be used as the Take Profit in percentage from the entry price level.
Use Custom Test Period: When enabled signals only works in the selected time window. If disabled it will use all historical data available on the chart.
Test Start and End: Once the Custom Test Period is enabled, here you select the start and end date that you want to analyze.
Check Messages: Check Messages: Enable this option to review the messages that will be sent to the bot.
Entry | TP | SL: Enable this options to send Buy Entry, Take Profit (TP), and Stop Loss (SL) signals.
Deal Entry and Deal Exit: Copy and paste the message for the deal start signal and close order at Market Price of the DCA Bot. This is the message that will be sent with the alert to the Bot, you must verify that it is the same as the bot so that it can process properly.
DCA Bot Multi-Pair: You must activate it if you want to use the signals in a DCA Bot Multi-pair in the text box you must enter (using the correct format) the symbol in which you are creating the alert, you can check the format of each symbol when you create the bot.
👨🏻💻💭 We hope this tool helps enhance your trading. Your feedback is invaluable, so feel free to share any suggestions for improvements or new features you'd like to see implemented.
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The information and publications within the 3Commas TradingView account are not meant to be and do not constitute financial, investment, trading, or other types of advice or recommendations supplied or endorsed by 3Commas and any of the parties acting on behalf of 3Commas, including its employees, contractors, ambassadors, etc.
Volume Delta Imbalance Index [PhenLabs]📊 Volume Delta Imbalance Index (VDII)
Version: PineScript™ v6
Description
The Volume Delta Imbalance Index is an advanced technical analysis tool that combines volume profile analysis with price movement dynamics to identify significant market imbalances. It features a sophisticated analysis system that weighs recent versus historical volume delta imbalance patterns, providing traders with insights into potential market reversals and trend continuation scenarios.
Points of Innovation:
Custom volume delta calculation incorporating price and volume relationships
Adaptive smoothing system based on market volatility
Multi-component analysis combining flow, acceleration, and strength metrics
Real-time volume profile integration with historical context
🔧 Core Components
Volume Profile Analysis: Dynamic volume delta imbalance distribution assessment
Flow Imbalance Detection: Buy/sell pressure evaluation
Strength Analysis: Composite market strength measurement
Acceleration Framework: Volume movement dynamics
Statistical Bands: Adaptive threshold system
🚨 Key Features 🚨
The indicator provides comprehensive analysis through:
Volume Delta: Up to date volume imbalance measurement
Market Structure: Support/resistance level identification
Flow Analysis: Buy/sell pressure visualization
Acceleration Signals: Movement momentum detection
Adaptive Bands: Dynamic overbought/oversold levels
📈 Visualization
Color-coded Columns: Shows direction and strength of imbalance
Signal Lines: Strong buy/sell level indicators
Statistical Bands: Shows normal trading ranges
Gradient Fills: Indicates extreme market conditions
Dynamic Opacity: Reflects trend strength
📌 Usage Guidelines
The indicator offers several customization options:
Basic Settings:
Lookback Period: Analysis timeframe adjustment
Sensitivity Level: Signal response calibration
History Depth: Historical context range
Memory Setting: Recent vs. historical data weight
Visual Settings:
Color Scheme: Bullish/bearish signal colors
Signal Levels: Strong buy/sell thresholds
Band Display: Statistical range visualization
✅ Best Use Cases / Things To Look For:
Wait for establishment in the initial trend when the VDII comes back towards zero and the color of the volume becomes more faint
Once this is established and the VDII pushes through to the other side look for small retracements above the zero line on the VDII leading you to believe it is a likely area for price to retrace and continue in its prior direction
Make sure you see the volume bars become more faint in color to give yo further confluence price will continue in its priorly established direction
⚠️ Limitations
Requires sufficient volume data
Most effective in liquid markets
Historical depth affects calculation speed
Possible lag in highly volatile conditions
What Makes This Unique
Composite Volume Analysis: Combines multiple volume metrics
Adaptive Calculation: Adjusts to market volatility
Profile Integration: Incorporates volume profile analysis
Multi-component Scoring: Weighted analysis system
Memory-efficient Design: Optimized for real-time analysis
🔧 How It Works
The indicator processes market data through four main components:
1. Volume Profile Analysis:
Creates dynamic volume delta distribution profiles
Weights recent versus historical data
Identifies significant price levels
2. Flow Imbalance Detection:
Analyzes buying versus selling pressure
Calculates normalized flow ratios
Determines market bias
3. Strength Analysis:
Measures composite market strength
Incorporates volume-weighted movements
Provides trend strength indication
4. Final Score Calculation:
Combines all components with weighted importance
Applies volatility-based smoothing
Generates final signal output
5. VDII Potential Reversal Confluences
Bars between signal confluence is default set to 10 but you can change it to whatever you’d prefer
Signals are a compiled look at the indicator as a whole determining where it think reversals or retracements are likely
💡 Note:
The indicator performs best in markets with consistent volume and clear trending or ranging conditions. Its sophisticated volume analysis provides valuable insights into market dynamics beyond traditional price-based indicators.
Nen Star Harmonic Pattern [TradingFinder] NenStar Reversal Auto🔵 Introduction
The Nen-Star Harmonic Pattern is an advanced reversal pattern in technical analysis, designed to identify market trend changes and predict key price reversal points. This pattern is defined by a combination of Fibonacci ratios and critical concepts such as Potential Reversal Zones (PRZ), market structure, and corrective waves.
The key points of this pattern include X, A, B, C, and D, and it appears in both bullish and bearish forms. In its bullish form, the pattern resembles the letter M, while in its bearish form, it takes the shape of W. The critical Fibonacci ratios for this pattern are 0.382 to 0.786 for the XA wave, 1.13 to 1.414 for the AB wave, and 1.272 to 2.618 for the BC wave.
The Nen-Star Harmonic Pattern is one of the most precise tools for identifying market reversals and executing reversal trades. Traders can use it to pinpoint optimal entry and exit points and benefit from high risk-to-reward ratios.
By emphasizing Fibonacci retracement levels, XABCD waves, the formation of bullish and bearish patterns, and precise trade entry points, this pattern has become a practical tool in advanced technical analysis.
Bullish Nen-Star Pattern :
Bearish Nen-Star Pattern :
🔵 How to Use
The Nen-Star Harmonic Pattern indicator allows traders to automatically identify the bullish and bearish structures of this pattern and locate optimal entry and exit points. By accurately analyzing Fibonacci ratios and determining points X, A, B, C, and D, the indicator highlights Potential Reversal Zones (PRZ) on the chart. Traders can rely on the generated signals to manage their trades with greater precision.
🟣 Bullish Nen-Star Pattern
The bullish Nen-Star pattern begins with a price increase from point X to point A, followed by a retracement to point B, which lies between 0.382 and 0.786 of the XA wave.
After this retracement, the price moves to point C, located between 1.13 and 1.414 of the AB wave. The final movement is a price decline to point D, which is between 1.272 and 2.618 of the BC wave and 1.13 to 1.272 of the XA wave.
Point D : Serves as the key Potential Reversal Zone (PRZ).
Entry : A buy trade is initiated at point D, signaling the end of the corrective movement and the beginning of a price increase.
Price Targets :
61.8% retracement of the CD wave
Point A
Point C
1.272 and 1.618 extensions of the CD wave if resistance at point C is broken
Stop Loss : Placed slightly below point D.
🟣 Bearish Nen-Star Pattern
The bearish Nen-Star pattern starts with a price decrease from point X to point A, followed by a retracement to point B, which lies between 0.382 and 0.786 of the XA wave.
After this retracement, the price moves to point C, located between 1.13 and 1.414 of the AB wave. The final movement is a price increase to point D, which is between 1.272 and 2.618 of the BC wave and 1.13 to 1.272 of the XA wave.
Point D : Serves as the key Potential Reversal Zone (PRZ).
Entry : A sell trade is initiated at point D, signaling the end of the corrective movement and the beginning of a price decline.
Price Targets :
61.8% retracement of the CD wave
Point A
Point C
1.272 and 1.618 extensions of the CD wave if support at point C is broken
Stop Loss : Placed slightly above point D.
🔵 Setting
🟣 Logical Setting
ZigZag Pivot Period : You can adjust the period so that the harmonic patterns are adjusted according to the pivot period you want. This factor is the most important parameter in pattern recognition.
Show Valid Forma t: If this parameter is on "On" mode, only patterns will be displayed that they have exact format and no noise can be seen in them. If "Off" is, the patterns displayed that maybe are noisy and do not exactly correspond to the original pattern.
Show Formation Last Pivot Confirm : if Turned on, you can see this ability of patterns when their last pivot is formed. If this feature is off, it will see the patterns as soon as they are formed. The advantage of this option being clear is less formation of fielded patterns, and it is accompanied by the latest pattern seeing and a sharp reduction in reward to risk.
Period of Formation Last Pivot : Using this parameter you can determine that the last pivot is based on Pivot period.
🟣 Genaral Setting
Show : Enter "On" to display the template and "Off" to not display the template.
Color : Enter the desired color to draw the pattern in this parameter.
LineWidth : You can enter the number 1 or numbers higher than one to adjust the thickness of the drawing lines. This number must be an integer and increases with increasing thickness.
LabelSize : You can adjust the size of the labels by using the "size.auto", "size.tiny", "size.smal", "size.normal", "size.large" or "size.huge" entries.
🟣 Alert Setting
Alert : On / Off
Message Frequency : This string parameter defines the announcement frequency. Choices include: "All" (activates the alert every time the function is called), "Once Per Bar" (activates the alert only on the first call within the bar), and "Once Per Bar Close" (the alert is activated only by a call at the last script execution of the real-time bar upon closing). The default setting is "Once per Bar".
Show Alert Time by Time Zone : The date, hour, and minute you receive in alert messages can be based on any time zone you choose. For example, if you want New York time, you should enter "UTC-4". This input is set to the time zone "UTC" by default.
🔵 Conclusion
The Nen-Star Harmonic Pattern is a highly effective analytical tool in global financial markets, playing a crucial role in identifying reversal points and market trend changes. By leveraging Fibonacci principles and price structure, this pattern enables precise analysis across various assets, including stocks, cryptocurrencies, forex, and commodities.
Traders operating in global markets can use this pattern to identify high risk-to-reward trading opportunities. Its clear entry and exit points, defined Potential Reversal Zones (PRZ), and accurate price targets make it an excellent tool for risk management and profitability enhancement.
In the global context, the Nen-Star pattern is widely used by professional analysts in both advanced and emerging markets due to its versatility in analyzing long-term and short-term charts. Beyond trend prediction, it enhances trading strategies and optimizes investment decisions.
Combining this pattern with complementary tools such as volume analysis, technical indicators, and macroeconomic conditions can provide traders with deeper market insights, helping them capitalize on global opportunities.
Regime Classifier Oscillator (AiBitcoinTrend)The Regime Classifier Oscillator (AiBitcoinTrend) is an advanced tool for understanding market structure and detecting dynamic price regimes. By combining filtered price trends, clustering algorithms, and an adaptive oscillator, it provides traders with detailed insights into market phases, including accumulation, distribution, advancement, and decline.
This innovative tool simplifies market regime classification, enabling traders to align their strategies with evolving market conditions effectively.
👽 What is a Regime Classifier, and Why is it Useful?
A Regime Classifier is a concept in financial analysis that identifies distinct market conditions or "regimes" based on price behavior and volatility. These regimes often correspond to specific phases of the market, such as trends, consolidations, or periods of high or low volatility. By classifying these regimes, traders and analysts can better understand the underlying market dynamics, allowing them to adapt their strategies to suit prevailing conditions.
👽 Common Uses in Finance
Risk Management: Identifying high-volatility regimes helps traders adjust position sizes or hedge risks.
Strategy Optimization: Traders tailor their approaches—trend-following strategies in trending regimes, mean-reversion strategies in consolidations.
Forecasting: Understanding the current regime aids in predicting potential transitions, such as a shift from accumulation to an upward breakout.
Portfolio Allocation: Investors allocate assets differently based on market regimes, such as increasing cash positions in high-volatility environments.
👽 Why It’s Important
Markets behave differently under varying conditions. A regime classifier provides a structured way to analyze these changes, offering a systematic approach to decision-making. This improves both accuracy and confidence in navigating diverse market scenarios.
👽 How We Implemented the Regime Classifier in This Indicator
The Regime Classifier Oscillator takes the foundational concept of market regime classification and enhances it with advanced computational techniques, making it highly adaptive.
👾 Median Filtering: We smooth price data using a custom median filter to identify significant trends while eliminating noise. This establishes a baseline for price movement analysis.
👾 Clustering Model: Using clustering techniques, the indicator classifies volatility and price trends into distinct regimes:
Advance: Strong upward trends with low volatility.
Decline: Downward trends marked by high volatility.
Accumulation: Consolidation phases with subdued volatility.
Distribution: Topping or bottoming patterns with elevated volatility.
This classification leverages historical price data to refine cluster boundaries dynamically, ensuring adaptive and accurate detection of market states.
Volatility Classification: Price volatility is analyzed through rolling windows, separating data into high and low volatility clusters using distance-based assignments.
Price Trends: The interaction of price levels with the filtered trendline and volatility clusters determines whether the market is advancing, declining, accumulating, or distributing.
👽 Dynamic Cycle Oscillator (DCO):
Captures cyclic behavior and overlays it with smoothed oscillations, providing real-time feedback on price momentum and potential reversals.
Regime Visualization:
Regimes are displayed with intuitive labels and background colors, offering clear, actionable insights directly on the chart.
👽 Why This Implementation Stands Out
Dynamic and Adaptive: The clustering and refit mechanisms adapt to changing market conditions, ensuring relevance across different asset classes and timeframes.
Comprehensive Insights: By combining price trends, volatility, and cyclic behaviors, the indicator provides a holistic view of the market.
This implementation bridges the gap between theoretical regime classification and practical trading needs, making it a powerful tool for both novice and experienced traders.
👽 Applications
👾 Regime-Based Trading Strategies
Traders can use the regime classifications to adapt their strategies effectively:
Advance & Accumulation: Favorable for entering or holding long positions.
Decline & Distribution: Opportunities for short positions or risk management.
👾 Oscillator Insights for Trend Analysis
Overbought/oversold conditions: Early warning of potential reversals.
Dynamic trends: Highlights the strength of price momentum.
👽 Indicator Settings
👾 Filter and Classification Settings
Filter Window Size: Controls trend detection sensitivity.
ATR Lookback: Adjusts the threshold for regime classification.
Clustering Window & Refit Interval: Fine-tunes regime accuracy.
👾 Oscillator Settings
Dynamic Cycle Oscillator Lookback: Defines the sensitivity of cycle detection.
Smoothing Factor: Balances responsiveness and stability.
Disclaimer: This information is for entertainment purposes only and does not constitute financial advice. Please consult with a qualified financial advisor before making any investment decisions.
Dollar Cost Averaging (YavuzAkbay)The Dollar Cost Averaging (DCA) indicator is designed to support long-term investors following a Dollar Cost Averaging strategy. The core aim of this tool is to provide insights into overbought and oversold levels, assisting investors in managing buy and sell decisions with a clear visual cue system. Specifically developed for use in trending or fluctuating markets, this indicator leverages support and resistance levels to give structure to investors' buying strategies. Here’s a detailed breakdown of the indicator’s key features and intended usage:
Key Features and Color Coding
Overbought/Oversold Detection:
The indicator shades candles from light green to dark green when an asset becomes increasingly overbought. Dark green signals indicate a peak, where the asset is overbought, suggesting a potential opportunity to take partial profits.
Conversely, candles turn from light red to dark red when the market is oversold. Dark red signifies a heavily oversold condition, marking an ideal buying window for initiating or adding to a position. This color scheme provides a quick visual reference for investors to manage entries and exits effectively.
Support and Resistance Levels:
To address the risk of assets falling further after an overbought signal, the DCA indicator dynamically calculates support and resistance levels. These levels guide investors on key price areas to watch for potential price reversals, allowing them to make more informed buying or selling decisions.
Support levels help investors assess whether they should divide their capital across multiple buy orders, starting at the current oversold zone and extending to anticipated support zones for maximum flexibility.
Usage Methodology
This indicator is intended for Dollar Cost Averaging, a method where investors gradually add to their position rather than entering all at once. Here’s how it complements the DCA approach:
Buy at Oversold Levels: When the indicator shows a dark red candle, it signals that the asset is oversold, marking an optimal entry point. The presence of support levels can help investors determine if they should fully invest their intended amount or stagger buys at potential lower levels.
Sell at Overbought Levels: When the indicator transitions to dark green, it suggests that the asset is overbought. This is an ideal time to consider selling a portion of holdings to realize gains. The resistance levels, marked by the indicator, offer guidance on where the price may encounter selling pressure, aiding investors in planning partial exits.
Customizable Settings
The DCA indicator offers several user-adjustable parameters:
Pivot Frequency and Source: Define the pivot point frequency and the source (candle wick or body) for more tailored support/resistance detection.
Maximum Pivot Points: Set the maximum number of pivot points to be used in support/resistance calculations, providing flexibility in adapting to different market structures.
Channel Width and Line Width: Adjust the width of the channel for support/resistance levels and the thickness of the lines for easier visual tracking.
Color Intensities for Overbought/Oversold Levels: Customize the shading intensity for each overbought and oversold level to align with your trading preferences.
Ichimoku Theories [LuxAlgo]The Ichimoku Theories indicator is the most complete Ichimoku tool you will ever need. Four tools combined into one to harness all the power of Ichimoku Kinkō Hyō.
This tool features the following concepts based on the work of Goichi Hosoda:
Ichimoku Kinkō Hyō: Original Ichimoku indicator with its five main lines and kumo.
Time Theory: automatic time cycle identification and forecasting to understand market timing.
Wave Theory: automatic wave identification to understand market structure.
Price Theory: automatic identification of developing N waves and possible price targets to understand future price behavior.
🔶 ICHIMOKU KINKŌ HYŌ
Ichimoku with lines only, Kumo only and both together
Let us start with the basics: the Ichimoku original indicator is a tool to understand the market, not to predict it, it is a trend-following tool, so it is best used in trending markets.
Ichimoku tells us what is happening in the market and what may happen next, the aim of the tool is to provide market understanding, not trading signals.
The tool is based on calculating the mid-point between the high and low of three pre-defined ranges as the equilibrium price for short (9 periods), medium (26 periods), and long (52 periods) time horizons:
Tenkan sen: middle point of the range of the last 9 candles
Kinjun sen: middle point of the range of the last 26 candles
Senkou span A: middle point between Tankan Sen and Kijun Sen, plotted 26 candles into the future
Senkou span B: midpoint of the range of the last 52 candles, plotted 26 candles into the future
Chikou span: closing price plotted 26 candles into the past
Kumo: area between Senkou pans A and B (kumo means cloud in Japanese)
The most basic use of the tool is to use the Kumo as an area of possible support or resistance.
🔶 TIME THEORY
Current cycles and forecast
Time theory is a critical concept used to identify historical and current market cycles, and use these to forecast the next ones. This concept is based on the Kihon Suchi (translating to "Basic Numbers" in Japanese), these are 9 and 26, and from their combinations we obtain the following sequence:
9, 17, 26, 33, 42, 51, 65, 76, 129, 172, 200, 257
The main idea is that the market moves in cycles with periods set by the Kihon Suchi sequence.
When the cycle has the same exact periods, we obtain the Taito Suchi (translating to "Same Number" in Japanese).
This tool allows traders to identify historical and current market cycles and forecast the next one.
🔹 Time Cycle Identification
Presentation of 4 different modes: SWINGS, HIGHS, KINJUN, and WAVES .
The tool draws a horizontal line at the bottom of the chart showing the cycles detected and their size.
The following settings are used:
Time Cycle Mode: up to 7 different modes
Wave Cycle: Which wave to use when WAVE mode is selected, only active waves in the Wave Theory settings will be used.
Show Time Cycles: keep a cleaner chart by disabling cycles visualisation
Show last X time cycles: how many cycles to display
🔹 Time Cycle Forecast
Showcasing the two forecasting patterns: Kihon Suchi and Taito Suchi
The tool plots horizontal lines, a solid anchor line, and several dotted forecast lines.
The following settings are used:
Show time cycle forecast: to keep things clean
Forecast Pattern: comes in two flavors
Kihon Suchi plots a line from the anchor at each number in the Kihon Suchi sequence.
Taito Suchi plot lines from the anchor with the same size detected in the anchored cycle
Anchor forecast on last X time cycle: traders can place the anchor in any detected cycle
🔶 WAVE THEORY
All waves activated with overlapping
The main idea behind this theory is that markets move like waves in the sea, back and forth (making swing lows and highs). Understanding the current market structure is key to having realistic expectations of what the market may do next. The waves are divided into Simple and Complex.
The following settings are used:
Basic Waves: allows traders to activate waves I, V and N
Complex Waves: allows traders to activate waves P, Y and W
Overlapping waves: to avoid missing out on any of the waves activated
Show last X waves: how many waves will be displayed
🔹 Basic Waves
The three basic waves
The basic waves from which all waves are made are I, V, and N
I wave: one leg moves
V wave: two legs move, one against the other
N wave: Three legs move, push, pull back, and another push
🔹 Complex Waves
Three complex waves
There are other waves like
P wave: contracting market
Y wave: expanding market
W wave: double top or double bottom
🔶 PRICE THEORY
All targets for the current N wave with their calculations
This theory is based on identifying developing N waves and predicting potential price targets based on that developing wave.
The tool displays 4 basic targets (V, E, N, and NT) and 3 extended targets (2E and 3E) according to the calculations shown in the chart above. Traders can enable or disable each target in the settings panel.
🔶 USING EVERYTHING TOGETHER
Please DON'T do this. This is not how you use it
Now the real example:
Daily chart of Nasdaq 100 futures (NQ1!) with our Ichimoku analysis
Time, waves, and price theories go together as one:
First, we identify the current time cycles and wave structure.
Then we forecast the next cycle and possible key price levels.
We identify a Taito Suchi with both legs of exactly 41 candles on each I wave, both together forming a V wave, the last two I waves are part of a developing N wave, and the time cycle of the first one is 191 candles. We forecast this cycle into the future and get 22nd April as a key date, so in 6 trading days (as of this writing) the market would have completed another Taito Suchi pattern if a new wave and time cycle starts. As we have a developing N wave we can see the potential price targets, the price is actually between the NT and V targets. We have a bullish Kumo and the price is touching it, if this Kumo provides enough support for the price to go further, the market could reach N or E targets.
So we have identified the cycle and wave, our expectations are that the current cycle is another Taito Suchi and the current wave is an N wave, the first I wave went for 191 candles, and we expect the second and third I waves together to amount to 191 candles, so in theory the N wave would complete in the next 6 trading days making a swing high. If this is indeed the case, the price could reach the V target (it is almost there) or even the N target if the bulls have the necessary strength.
We do not predict the future, we can only aim to understand the current market conditions and have future expectations of when (time), how (wave), and where (price) the market will make the next turning point where one side of the market overcomes the other (bulls vs bears).
To generate this chart, we change the following settings from the default ones:
Swing length: 64
Show lines: disabled
Forecast pattern: TAITO SUCHI
Anchor forecast: 2
Show last time cycles: 5
I WAVE: enabled
N WAVE: disabled
Show last waves: 5
🔶 SETTINGS
Show Swing Highs & Lows: Enable/Disable points on swing highs and swing lows.
Swing Length: Number of candles to confirm a swing high or swing low. A higher number detects larger swings.
🔹 Ichimoku Kinkō Hyō
Show Lines: Enable/Disable the 5 Ichimoku lines: Kijun sen, Tenkan sen, Senkou span A & B and Chikou Span.
Show Kumo: Enable/Disable the Kumo (cloud). The Kumo is formed by 2 lines: Senkou Span A and Senkou Span B.
Tenkan Sen Length: Number of candles for Tenkan Sen calculation.
Kinjun Sen Length: Number of candles for the Kijun Sen calculation.
Senkou Span B Length: Number of candles for Senkou Span B calculation.
Chikou & Senkou Offset: Number of candles for Chikou and Senkou Span calculation. Chikou Span is plotted in the past, and Senkou Span A & B in the future.
🔹 Time Theory
Show Time Cycle Forecast: Enable/Disable time cycle forecast vertical lines. Disable for better performance.
Forecast Pattern: Choose between two patterns: Kihon Suchi (basic numbers) or Taito Suchi (equal numbers).
Anchor forecast on last X time cycle: Number of time cycles in the past to anchor the time cycle forecast. The larger the number, the deeper in the past the anchor will be.
Time Cycle Mode: Choose from 7 time cycle detection modes: Tenkan Sen cross, Kijun Sen cross, Kumo change between bullish & bearish, swing highs only, swing lows only, both swing highs & lows and wave detection.
Wave Cycle: Choose which type of wave to detect from 6 different wave types when the time cycle mode is set to WAVES.
Show Time Cycles: Enable/Disable time cycle horizontal lines. Disable for better performance.
how last X time cycles: Maximum number of time cycles to display.
🔹 Wave Theory
Basic Waves: Enable/Disable the display of basic waves, all at once or one at a time. Disable for better performance.
Complex Waves: Enable/Disable complex wave display, all at once or one by one. Disable for better performance.
Overlapping Waves: Enable/Disable the display of waves ending on the same swing point.
Show last X waves: 'Maximum number of waves to display.
🔹 Price Theory
Basic Targets: Enable/Disable horizontal price target lines. Disable for better performance.
Extended Targets: Enable/Disable extended price target horizontal lines. Disable for better performance.
Protected Highs & Lows [TFO]This indicator presents an alternative approach to identify Market Structure. The logic used is derived from learning material created by @DaveTeaches
When quantifying Market Structure, it is common to use fractal highs and lows to identify "significant" swing pivots. When price closes through these pivots, we may identify a Market Structure Shift (MSS) for reversals or a Break of Structure (BOS) for continuations. The main difference with this "protected" logic is in how we determine the pivots/levels that are utilized to determine a valid MSS or BOS.
Nonetheless, the significance of our swing pivots is still governed by the input Pivot Strength parameter, which requires valid swing pivots to be compared to this many bars to the left and right of them. This is an optional parameter as it is traditionally set to 1 by default.
When identifying a BOS: When price closes below a valid swing low, we look back from the current bar to find the highest high that was made in that range. This becomes our protected high; similarly, when price closes above a valid swing high, we look back from the current bar to find the lowest low that was made in that range, which then becomes our protected low.
Note these valid highs and lows are the first swing pivots created after a MSS/BOS. For example, when price makes a bullish BOS/MSS and then trades away, a swing high is formed. This first swing high is what needs to be traded through to see a valid BOS.
When identifying a MSS: If the current trend is bearish and we're looking for a bullish reversal, we would need price to close above the most recent protected high. When this happens, we still look back to find the lowest low that was created in that range, and make that our new protected low. Likewise when looking for a bearish reversal, price would need to close below the most recent protected low, which would then give us a new protected high as a result (the highest point in that range).
The Trend Candles option allows users to easily visualize the current state of Market Structure with bullish and bearish colors. Users may also show BOS and MSS labels if desired.
Show Protected Highs & Lows will annotate the protected highs and lows, just note that the labels themselves are plotted in the past due to the lookback function required to identify them.
Lastly, the Show Protected Trail option will draw a line to essentially indicate a trailing stop-like line to denote the most recent protected low (if bullish) or protected high (if bearish).
I am simply a student of Dave's concepts, so please feel free to leave feedback if you are familiar with his concepts and have suggestions/improvements.
Physics CandlesPhysics Candles embed volume and motion physics directly onto price candles or market internals according to the cyclic pattern of financial securities. The indicator works on both real-time “ticks” and historical data using statistical modeling to highlight when these values, like volume or momentum, is unusual or relatively high for some periodic window in time. Each candle is made out of one or more sub-candles that each contain their own information of motion, which converts to the color and transparency, or brightness, of that particular candle segment. The segments extend throughout the entire candle, both body and wicks, and Thick Wicks can be implemented to see the color coding better. This candle segmentation allows you to see if all the volume or energy is evenly distributed throughout the candle or highly contained in one small portion of it, and how intense these values are compared to similar time periods without going to lower time frames. Candle segmentation can also change a trader’s perspective on how valuable the information is. A “low” volume candle, for instance, could signify high value short-term stopping volume if the volume is all concentrated in one segment.
The Candles are flexible. The physics information embedded on the candles need not be from the same price security or market internal as the chart when using the Physics Source option, and multiple Candles can be overlayed together. You could embed stock price Candles with market volume, market price Candles with stock momentum, market structure with internal acceleration, stock price with stock force, etc. My particular use case is scalping the SPX futures market (ES), whose price action is also dictated by the volume action in the associated cash market, or SPY, as well as a host of other securities. Physics allows you to embed the ES volume on the SPY price action, or the SPY volume on the ES price action, or you can combine them both by overlaying two Candle streams and increasing the Number of Overlays option to two. That option decreases the transparency levels of your coloring scheme so that overlaying multiple Candles converges toward the same visual color intensity as if you had one. The Candle and Physics Sources allows for both Symbols and Spreads to visualize Candle physics from a single ticker or some mathematical transformation of tickers.
Due to certain TradingView programming restrictions, each Candle can only be made out of a maximum of 8 candle segments, or an “8-bit” resolution. Since limits are just an opportunity to go beyond, the user has the option to stack multiple Candle indicators together to further increase the candle resolution. If you don’t want to see the Candles for some particular period of the day, you can hide them, or use the hiding feature to have multiple Candles calibrated to show multiple parts of the trading day. Securities tend to have low volume after hours with sharp spikes at the open or close. Multiple Candles can be used for multiple parts of the trading day to accommodate these different cycles in volume.
The Candles do not need be associated with the nominal security listed on the TV chart. The Candle Source allows the user to look at AAPL Candles, for instance, while on a TSLA or SPY chart, each with their respective volume actions integrated into the candles, for instance, to allow the user to see multiple security price and volume correlation on a single chart.
The physics information currently embeddable on Candles are volume or time, velocity, momentum, acceleration, force, and kinetic energy. In order to apply equations of motion containing a mass variable to financial securities, some analogous value for mass must be assumed. Traders often regard volume or time as inextricable variables to a securities price that can indicate the direction and strength of a move. Since mass is the inextricable variable to calculating the momentum, force, or kinetic energy of motion, the user has the option to assume either time or volume is analogous to mass. Volume may be a better option for mass as it is not strictly dependent on the speed of a security, whereas time is.
Data transformations and outlier statistics are used to color code the intensity of the physics for each candle segment relative to past periodic behavior. A million shares during pre-market or a million shares during noontime may be more intense signals than a typical million shares traded at the open, and should have more intense color signals. To account for a specific cyclic behavior in the market, the user can specify the Window and Cycle Time Frames. The Window Time Frame splits up a Cycle into windows, samples and aggregates the statistics for each window, then compares the current physics values against past values in the same window. Intraday traders may benefit from using a Daily Cycle with a 30-minute Window Time Frame and 1-minute Sample Time Frame. These settings sample and compare the physics of 1-minute candles within the current 30-minute window to the same 30-minute window statistics for all past trading days, up until the data limit imposed by TradingView, or until the Data Collection Start Date specified in the settings. Longer-term traders may benefit from using a Monthly Cycle with a Weekly Time Frame, or a Yearly Cycle with a Quarterly Time Frame.
Multiple statistics and data transformation methods are available to convey relative intensity in different ways for different trading signals. Physics Candles allows for both Normal and Log-Normal assumptions in the physics distribution. The data can then be transformed by Linear, Logarithmic, Z-Score, or Power-Law scoring, where scoring simply assigns an intensity to the relative physics value of each candle segment based on some mathematical transformation. Z-scoring often renders adequate detection by scoring the segment value, such as volume or momentum, according to the mean and standard deviation of the data set in each window of the cycle. Logarithmic or power-law transformation with a gamma below 1 decreases the disparity between intensities so more less-important signals will show up, whereas the power-law transformation with gamma values above 1 increases the disparity between intensities, so less more-important signals will show up. These scores are then converted to color and transparency between the Min Score and the Max Score Cutoffs. The Auto-Normalization feature can automatically pick these cutoffs specific to each window based on the mean and standard deviation of the data set, or the user can manually set them. Physics was developed with novices in mind so that most users could calibrate their own settings by plotting the candle segment distributions directly on the chart and fiddling with the settings to see how different cutoffs capture different portions of the distribution and affect the relative color intensities differently. Security distributions are often skewed with fat-tails, known as kurtosis, where high-volume segments for example, have a higher-probabilities than expected for a normal distribution. These distribution are really log-normal, so that taking the logarithm leads to a standard bell-shaped distribution. Taking the Z-score of the Log-Normal distribution could make the most statistical sense, but color sensitivity is a discretionary preference.
Background Philosophy
This indicator was developed to study and trade the physics of motion in financial securities from a visually intuitive perspective. Newton’s laws of motion are loosely applied to financial motion:
“A body remains at rest, or in motion at a constant speed in a straight line, unless acted upon by a force”.
Financial securities remain at rest, or in motion at constant speed up or down, unless acted upon by the force of traders exchanging securities.
“When a body is acted upon by a force, the time rate of change of its momentum equals the force”.
Momentum is the product of mass and velocity, and force is the product of mass and acceleration. Traders render force on the security through the mass of their trading activity and the acceleration of price movement.
“If two bodies exert forces on each other, these forces have the same magnitude but opposite directions.”
Force arises from the interaction of traders, buyers and sellers. One body of motion, traders’ capitalization, exerts an equal and opposite force on another body of motion, the financial security. A securities movement arises at the expense of a buyer or seller’s capitalization.
Volume
The premise of this indicator assumes that volume, v, is an analogous means of measuring physical mass, m. This premise allows the application of the equations of motion to the movement of financial securities. We know from E=mc^2 that mass has energy. Energy can be used to create motion as kinetic energy. Taking a simple hypothetical example, the interaction of one short seller looking to cover lower and one buyer looking to sell higher exchange shares in a security at an agreed upon price to create volume or mass, and therefore, potential energy. Eventually the short seller will actively cover and buy the security from the previous buyer, moving the security higher, or the buyer will actively sell to the short seller, moving the security lower. The potential energy inherent in the initial consolidation or trading activity between buy and seller is now converted to kinetic energy on the subsequent trading activity that moves the securities price. The more potential energy that is created in the consolidation, the more kinetic energy there is to move price. This is why point and figure traders are said to give price targets based on the level of volatility or size of a consolidation range, or why Gann traders square price and time, as time is roughly proportional to mass and trading activity. The build-up of potential energy between short sellers and buyers in GME or TSLA led to their explosive moves beyond their standard fundamental valuations.
Position
Position, p, is simply the price or value of a financial security or market internal.
Time
Time, t, is another means of measuring mass to discover price behavior beyond the time snapshots that simple candle charts provide. We know from E=mc^2 that time is related to rest mass and energy given the speed of light, c, where time ≈ distance * sqrt(mass/E). This relation can also be derived from F=ma. The more mass there is, the longer it takes to compute the physics of a system. The more energy there is, the shorter it takes to compute the physics of a system. Similarly, more time is required to build a “resting” low-volatility trading consolidation with more mass. More energy added to that trading consolidation by competing buyers and sellers decreases the time it takes to build that same mass. Time is also related to price through velocity.
Velocity = (p(t1) – p(t0)) / p(t0)
Velocity, v, is the relative percent change of a securities price, p, over a period of time, t0 to t1. The period of time is between subsequent candles, and since time is constant between candles within the same timeframe, it is not used to calculate velocity or acceleration. Price moves faster with higher velocity, and slower with slower velocity, over the same fixed period of time. The product of velocity and mass gives momentum.
Momentum = mv
This indicator uses physics definition of momentum, not finance’s. In finance, momentum is defined as the amount of change in a securities price, either relative or absolute. This is definition is unfortunate, pun intended, since a one dollar move in a security from a thousand shares traded between a few traders has the exact same “momentum” as a one dollar move from millions of shares traded between hundreds of traders with everything else equal. If momentum is related to the energy of the move, momentum should consider both the level of activity in a price move, and the amount of that price move. If we equate mass to volume to account for the level of trading activity and use physics definition of momentum as the product of mass and velocity, this revised definition now gives a thousand-times more momentum to a one-dollar price move that has a thousand-times more volume behind it. If you want to use finance’s volume-less definition of momentum, use velocity in this indicator.
Acceleration = v(t1) – v(t0)
Acceleration, a, is the difference between velocities over some period of time, t0 to t1. Positive acceleration is necessary to increase a securities speed in the positive direction, while negative acceleration is necessary to decrease it. Acceleration is related to force by mass.
Force = ma
Force is required to change the speed of a securities valuation. Price movements with considerable force have considerably more impact on future direction. A change in direction requires force.
Kinetic Energy = 0.5mv^2
Kinetic energy is the energy that a financial security gains from the change in its velocity by force. The built-up of potential energy in trading consolidations can be converted to kinetic energy on a breakout from the consolidation.
Cycle Theory and Relativity
Just as the physics of motion is relative to a point of reference, so too should the physics of financial securities be relative to a point of reference. An object moving at a 100 mph towards another object moving in the same direction at 100 mph will not appear to be moving relative to each other, nor will they collide, but from an outsider observer, the objects are going 100 mph and will collide with significant impact if they run into a stationary object relative to the observer. Similarly, trading with a hundred thousand shares at the open when the average volume is a couple million may have a much smaller impact on the price compared to trading a hundred thousand shares pre-market when the average volume is ten thousand shares. The point of reference used in this indicator is the average statistics collected for a given Window Time Frame for every Cycle Time Frame. The physics values are normalized relative to these statistics.
Examples
The main chart of this publication shows the Force Candles for the SPY. An intense force candle is observed pre-market that implicates the directional overtone of the day. The assumption that direction should follow force arises from physical observation. If a large object is accelerating intensely in a particular direction, it may be fair to assume that the object continues its direction for the time being unless acted upon by another force.
The second example shows a similar Force Candle for the SPY that counters the assumption made in the first example and emphasizes the importance of both motion and context. While it’s fair to assume that a heavy highly accelerating object should continue its course, if that object runs into an obstacle, say a brick wall, it’s course may deviate. This example shows SPY running into the 50% retracement wall from the low of Mar 2020, a significant support level noted in literature. The example also conveys Gann’s idea of “lost motion”, where the SPY penetrated the 50% price but did not break through it. A brick wall is not one atom thick and price support is not one tick thick. An object can penetrate only one layer of a wall and not go through it.
The third example shows how Volume Candles can be used to identify scalping opportunities on the SPY and conveys why price behavior is as important as motion and context. It doesn’t take a brick wall to impede direction if you know that the person driving the car tends to forget to feed the cats before they leave. In the chart below, the SPY breaks down to a confluence of the 5-day SMA, 20-day SMA, and an important daily trendline (not shown) after the bullish bounce from the 50% retracement days earlier. High volume candles on the SMA signify stopping volume that reverse price direction. The character of the day changes. Bulls become more aggressive than bears with higher volume on upswings and resistance, whiles bears take on a defensive position with lower volume on downswings and support. High volume stopping candles are seen after rallies, and can tell you when to take profit, get out of a position, or go short. The character change can indicate that its relatively safe to re-enter bullish positions on many major supports, especially given the overarching bullish theme from the large reaction off the 50% retracement level.
The last example emphasizes the importance of relativity. The Volume Candles in the chart below are brightest pre-market even though the open has much higher volume since the pre-market activity is much higher compared to past pre-markets than the open is compared to past opens. Pre-market behavior is a good indicator for the character of the day. These bullish Volume Candles are some of the brightest seen since the bounce off the 50% retracement and indicates that bulls are making a relatively greater attempt to bring the SPY higher at the start of the day.
Infrequently Asked Questions
Where do I start?
The default settings are what I use to scalp the SPY throughout most of the extended trading day, on a one-minute chart using SPY volume. I also overlay another Candle set containing ES future volume on the SPY price structure by setting the Physics Source to ES1! and the Number of Overlays setting to 2 for each Candle stream in order to account for pre- and post-market trading activity better. Since the closing volume is exponential-like up until the end of the regular trading day, adding additional Candle streams with a tighter Window Time Frame (e.g., 2-5 minute) in the last 15 minutes of trading can be beneficial. The Hide feature can allow you to set certain intraday timeframes to hide one Candle set in order to show another Candle set during that time.
How crazy can you get with this indicator?
I hope you can answer this question better. One interesting use case is embedding the velocity of market volume onto an internal market structure. The PCTABOVEVWAP.US is a market statistic that indicates the percent of securities above their VWAP among US stocks and is helpful for determining short term trends in the US market. When securities are rising above their VWAP, the average long is up on the day and a rising PCTABOVEVWAP.US can be viewed as more bullish. When securities are falling below their VWAP, the average short is up on the day and a falling PCTABOVEVWAP.US can be viewed as more bearish. (UPVOL.US - DNVOL.US) / TVOL.US is a “spread” symbol, in TV parlance, that indicates the decimal percent difference between advancing volume and declining volume in the US market, showing the relative flow of volume between stocks that are up on the day, and stocks that are down on the day. Setting PCTABOVEVWAP.US in the Candle Source, (UPVOL.US - DNVOL.US) / TVOL.US in the Physics Source, and selecting the Physics to Velocity will embed the relative velocity of the spread symbol onto the PCTABOVEVWAP.US candles. This can be helpful in seeing short term trends in the US market that have an increasing amount of volume behind them compared to other trends. The chart below shows Volume Candles (top) and these Spread Candles (bottom). The first top at 9:30 and second top at 10:30, the high of the day, break down when the spread candles light up, showing a high velocity volume transfer from up stocks to down stocks.
How do I plot the indicator distribution and why should I even care?
The distribution is visually helpful in seeing how different normalization settings effect the distribution of candle segments. It is also helpful in seeing what physics intensities you want to ignore or show by segmenting part of the distribution within the Min and Max Cutoff values. The intensity of color is proportional to the physics value between the Min and Max Cutoff values, which correspond to the Min and Max Colors in your color scheme. Any physics value outside these Min and Max Cutoffs will be the same as the Min and Max Colors.
Select the Print Windows feature to show the window numbers according to the Cycle Time Frame and Window Time Frame settings. The window numbers are labeled at the start of each window and are candle width in size, so you may need to zoom into to see them. Selecting the Plot Window feature and input the window number of interest to shows the distribution of physics values for that particular window along with some statistics.
A log-normal volume distribution of segmented z-scores is shown below for 30-minute opening of the SPY. The Min and Max Cutoff at the top of the graph contain the part of the distribution whose intensities will be linearly color-coded between the Min and Max Colors of the color scheme. The part of the distribution below the Min Cutoff will be treated as lowest quality signals and set to the Min Color, while the few segments above the Max Cutoff will be treated as the highest quality signals and set to the Max Color.
What do I do if I don’t see anything?
Troubleshooting issues with this indicator can involve checking for error messages shown near the indicator name on the chart or using the Data Validation section to evaluate the statistics and normalization cutoffs. For example, if the Plot Window number is set to a window number that doesn’t exist, an error message will tell you and you won’t see any candles. You can use the Print Windows option to show windows that do exist for you current settings. The auto-normalization cutoff values may be inappropriate for your particular use case and literally cut the candles out of the chart. Try changing the chart time frame to see if they are appropriate for your cycle, sample and window time frames. If you get a “Timeframe passed to the request.security_lower_tf() function must be lower than the timeframe of the main chart” error, this means that the chart timeframe should be increased above the sample time frame. If you get a “Symbol resolve error”, ensure that you have correct symbol or spread in the Candle or Physics Source.
How do I see a relative physics values without cycles?
Set the Window Time Frame to be equal to the Cycle Time Frame. This will aggregate all the statistics into one bucket and show the physics values, such as volume, relative to all the past volumes that TV will allow.
How do I see candles without segmentation?
Segmentation can be very helpful in one context or annoying in another. Segmentation can be removed by setting the candle resolution value to 1.
Notes
I have yet to find a trading platform that consistently provides accurate real-time volume and pricing information, lacking adequate end-user data validation or quality control. I can provide plenty of examples of real-time volume counts or prices provided by TradingView and other platforms that were significantly off from what they should have been when comparing against the exchanges own data, and later retroactively corrected or not corrected at all. Since no indicator can work accurately with inaccurate data, please use at your own discretion.
The first version is a beta version. Debugging and validating code in Pine script is difficult without proper unit testing. Please report any bugs with enough information to reproduce them and indicate why they are important. I also encourage you to export the data from TradingView and verify the calculations for your particular use case.
The indicator works on real-time updates that occur at a higher frequency than the candle time frame, which TV incorrectly refers to as ticks. They use this terminology inaccurately as updates are really aggregated tick data that can take place at different prices and may not accurately reflect the real tick price action. Consequently, this inaccuracy also impacts the real-time segmentation accuracy to some degree. TV does not provide a means of retaining “tick” information, so the higher granularity of information seen real-time will be lost on a disconnect.
TV does not provide time and sales information. The volume and price information collected using the Sample Time Frame is intraday, which provides only part of the picture. Intraday volume is generally 50 to 80% of the end of day volume. Consequently, the daily+ OHLC prices are intraday, and may differ significantly from exchanged settled OHLC prices.
The Cycle and Window Time Frames refer to calendar days and time, not trading days or time. For example, the first window week of a monthly cycle is the first seven days of the month, not the first Monday through Friday of trading for the month.
Chart Time Frames that are higher than the Window Time Frames average the normalized physics for price action that occurred within a given Candle segment. It does not average price action that did not occur.
One of the main performance bottleneck in TradingView’s Pine Script is client-side drawing and plotting. The performance of this indicator can be increased by lowering the resolution (the number of sub-candles this indicator plots), getting a faster computer, or increasing the performance of your computer like plugging your laptop in and eliminating unnecessary processes.
The statistical integrity of this indicator relies on the number of samples collected per sample window in a given cycle. Higher sample counts can be obtained by increasing the chart time frame or upgrading the TradingView plan for a higher bar count. While increasing the chart time frame doesn’t increase the visual number of bars plotted on the chart, it does increase the number of bars that can be pulled at a lower time frame, up to 100,000.
Due to a limitation in Pine Scripts request_lower_tf() function, using a spread symbol will only work for regular trading hours, not extended trading hours.
Ideally, velocity or momentum should be calculated between candle closes. To eliminate the need to deal with price gaps that would lead to an incorrect statistical distributions, momentum is calculated between candle open and closes as a percent change of the price or value, which should not be an issue for most liquid securities.
Time-based LiquidityThis indicator automatically marks important time-based liquidity levels on your chart, helping you stay aware of where major price reactions may occur and the market is forced to show its hand.
Key Features:
Previous Month’s, Week’s, and Day’s Highs and Lows: Displays PMH/PML, PWH/PWL, and PDH/PDL — key reference points where liquidity often accumulates.
Intraday Session Highs and Lows: Divides the trading day into quarters (00:00–06:00, 06:00–12:00, etc. following Day’s Quarterly Theory) and tracks session highs and lows dynamically across these periods.
Current Session 90-Minute Quarters: Splits the active session into 90-minute intervals to highlight short-term liquidity structures and potential reaction zones.
Level Alerts: Tracks when each liquidity level is reached and enables customizable alerts so you don’t miss important price movements.
Use Case:
This tool provides an organized, time-based framework for identifying where liquidity is likely to concentrate across different timeframes and intraday cycles. Use these levels for forming bias, planning entries, exits, or anticipating price reactions at key points in the market structure.
Customization Options:
Enable/disable liquidity levels to display (Daily, Weekly, Monthly, Sessions, Session Quarters)
Customize the appearance of each level (color, style, line width)
Enable or disable tracking and alerts for level interactions
OA - PowerZones Support And ResistancePowerZones - Dynamic Support/Resistance Identifier
Overview
PowerZones is an advanced technical analysis tool that automatically detects significant support and resistance zones using volume data and pivot points. This indicator pulls data from higher timeframes (weekly by default) to help you identify strong and meaningful levels that are filtered from short-term "noise."
Features
Multi-Timeframe Analysis: Create support/resistance levels from daily, weekly, or monthly data
Volume Filtering: Detect high-volume pivot points to identify more reliable levels
Dynamic Threshold: Volume filter that automatically adjusts to market conditions
Visual Clarity: Support/resistance zones are displayed as boxes with adjustable transparency
Optimal Level Selection: Filter out close levels to focus on the most significant support/resistance points
Use Cases
Entry/Exit Points: Identify trading opportunities at important support and resistance levels
Stop-Loss Placement: Use natural support levels to set more effective stop-losses
Target Setting: Use potential resistance levels as profit-taking targets
Understanding Market Structure: Detect long-term support/resistance zones to better interpret price movement
Input Parameters
Lookback Period: The period used to determine pivot points
Box Width : Adjusts the width of support/resistance zones
Relative Volume Period: The period used for relative volume calculation
Maximum Number of Boxes: Maximum number of support/resistance zones to display on the chart
Box Transparency: Transparency value for the boxes
Timeframe: Timeframe to use for support/resistance detection (Daily, Weekly, Monthly)
How It Works
PowerZones identifies pivot highs and lows in the selected timeframe. It filters these points using volume data to show only meaningful and strong levels. The indicator also consolidates nearby levels, allowing you to focus only on the most important zones on the chart.
Best Practices
Weekly timeframe setting is ideal for identifying long-term important support/resistance levels
Working with weekly levels on a daily chart allows you to combine long-term levels with short-term trades
ATR-based box width creates support/resistance zones that adapt to market volatility
Use the indicator along with other technical indicators such as RSI, MACD, or moving averages to confirm trading signals
Note: Like all technical indicators, this indicator does not guarantee 100% accuracy. Always apply risk management principles and use it in conjunction with other analysis methods to achieve the best results.
If you like the PowerZones indicator, please show your support by giving it a star and leaving a comment!
ICT & SMC Multi-Timeframe by [KhedrFX]Transform your trading experience with the ICT & SMC Multi-Timeframe by indicator. This innovative tool is designed for traders who want to harness the power of multi-timeframe analysis, enabling them to make informed trading decisions based on key market insights. By integrating concepts from the Inner Circle Trader (ICT) and Smart Money Concepts (SMC), this indicator provides a comprehensive view of market dynamics, helping you identify potential trading opportunities with precision.
Key Features
- Multi-Timeframe Analysis: Effortlessly switch between various timeframes (5 minutes, 15 minutes, 30 minutes, 1 hour, 4 hours, daily, and weekly) to capture the full spectrum of market movements.
- High and Low Levels: Automatically calculates and displays the highest and lowest price levels over the last 20 bars, highlighting critical support and resistance zones.
- Market Structure Visualization: Identifies the last swing high and swing low, allowing you to recognize current market trends and potential reversal points.
- Order Block Detection: Detects significant order blocks, pinpointing areas of strong buying or selling pressure that can indicate potential market reversals.
- Custom Alerts: Set alerts for when the price crosses above or below identified order block levels, enabling you to act swiftly on trading opportunities.
How to Use the Indicator
1. Add the Indicator to Your Chart
- Open TradingView.
- Click on the "Indicators" button at the top of the screen.
- Search for "ICT & SMC Multi-Timeframe by " in the search bar.
- Click on the indicator to add it to your chart.
2. Select Your Timeframe
- Use the dropdown menu to choose your preferred timeframe (5, 15, 30, 60, 240, D, W) for analysis.
3. Interpret the Signals
- High Level (Green Line): Represents the highest price level over the last 20 bars, acting as a potential resistance level.
- Low Level (Red Line): Represents the lowest price level over the last 20 bars, acting as a potential support level.
- Last Swing High (Blue Cross): Indicates the most recent significant high, useful for identifying potential reversal points.
- Last Swing Low (Orange Cross): Indicates the most recent significant low, providing insight into market structure.
- Order Block High (Purple Line): Marks the upper boundary of a detected order block, suggesting potential selling pressure.
- Order Block Low (Yellow Line): Marks the lower boundary of a detected order block, indicating potential buying pressure.
4. Set Alerts
- Utilize the alert conditions to receive notifications when the price crosses above or below the order block levels, allowing you to stay informed about potential trading opportunities.
5. Implement Risk Management
- Always use proper risk management techniques. Consider setting stop-loss orders based on the identified swing highs and lows or the order block levels to protect your capital.
Conclusion
The ICT & SMC Multi-Timeframe by indicator is an essential tool for traders looking to enhance their market analysis and decision-making process. By leveraging multi-timeframe insights, market structure visualization, and order block detection, you can navigate the complexities of the market with confidence. Start using this powerful indicator today and take your trading to the next level.
⚠️ Trade Responsibly
This tool helps you analyze the market, but it’s not a guarantee of profits. Always do your own research, manage risk, and trade with caution.
Adaptive Fibonacci Pullback System -FibonacciFluxAdaptive Fibonacci Pullback System (AFPS) - FibonacciFlux
This work is licensed under a Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0). Original concepts by FibonacciFlux.
Abstract
The Adaptive Fibonacci Pullback System (AFPS) presents a sophisticated, institutional-grade algorithmic strategy engineered for high-probability trend pullback entries. Developed by FibonacciFlux, AFPS uniquely integrates a proprietary Multi-Fibonacci Supertrend engine (0.618, 1.618, 2.618 ratios) for harmonic volatility assessment, an Adaptive Moving Average (AMA) Channel providing dynamic market context, and a synergistic Multi-Timeframe (MTF) filter suite (RSI, MACD, Volume). This strategy transcends simple indicator combinations through its strict, multi-stage confluence validation logic. Historical simulations suggest that specific MTF filter configurations can yield exceptional performance metrics, potentially achieving Profit Factors exceeding 2.6 , indicative of institutional-level potential, while maintaining controlled risk under realistic trading parameters (managed equity risk, commission, slippage).
4 hourly MTF filtering
1. Introduction: Elevating Pullback Trading with Adaptive Confluence
Traditional pullback strategies often struggle with noise, false signals, and adapting to changing market dynamics. AFPS addresses these challenges by introducing a novel framework grounded in Fibonacci principles and adaptive logic. Instead of relying on static levels or single confirmations, AFPS seeks high-probability pullback entries within established trends by validating signals through a rigorous confluence of:
Harmonic Volatility Context: Understanding the trend's stability and potential turning points using the unique Multi-Fibonacci Supertrend.
Adaptive Market Structure: Assessing the prevailing trend regime via the AMA Channel.
Multi-Dimensional Confirmation: Filtering signals with lower-timeframe Momentum (RSI), Trend Alignment (MACD), and Market Conviction (Volume) using the MTF suite.
The objective is to achieve superior signal quality and adaptability, moving beyond conventional pullback methodologies.
2. Core Methodology: Synergistic Integration
AFPS's effectiveness stems from the engineered synergy between its core components:
2.1. Multi-Fibonacci Supertrend Engine: Utilizes specific Fibonacci ratios (0.618, 1.618, 2.618) applied to ATR, creating a multi-layered volatility envelope potentially resonant with market harmonics. The averaged and EMA-smoothed result (`smoothed_supertrend`) provides a robust, dynamic trend baseline and context filter.
// Key Components: Multi-Fibonacci Supertrend & Smoothing
average_supertrend = (supertrend1 + supertrend2 + supertrend3) / 3
smoothed_supertrend = ta.ema(average_supertrend, st_smooth_length)
2.2. Adaptive Moving Average (AMA) Channel: Provides dynamic market context. The `ama_midline` serves as a key filter in the entry logic, confirming the broader trend bias relative to adaptive price action. Extended Fibonacci levels derived from the channel width offer potential dynamic S/R zones.
// Key Component: AMA Midline
ama_midline = (ama_high_band + ama_low_band) / 2
2.3. Multi-Timeframe (MTF) Filter Suite: An optional but powerful validation layer (RSI, MACD, Volume) assessed on a lower timeframe. Acts as a **validation cascade** – signals must pass all enabled filters simultaneously.
2.4. High-Confluence Entry Logic: The core innovation. A pullback entry requires a specific sequence and validation:
Price interaction with `average_supertrend` and recovery above/below `smoothed_supertrend`.
Price confirmation relative to the `ama_midline`.
Simultaneous validation by all enabled MTF filters.
// Simplified Long Entry Logic Example (incorporates key elements)
long_entry_condition = enable_long_positions and
(low < average_supertrend and close > smoothed_supertrend) and // Pullback & Recovery
(close > ama_midline and close > ama_midline) and // AMA Confirmation
(rsi_filter_long_ok and macd_filter_long_ok and volume_filter_ok) // MTF Validation
This strict, multi-stage confluence significantly elevates signal quality compared to simpler pullback approaches.
1hourly filtering
3. Realistic Implementation and Performance Potential
AFPS is designed for practical application, incorporating realistic defaults and highlighting performance potential with crucial context:
3.1. Realistic Default Strategy Settings:
The script includes responsible default parameters:
strategy('Adaptive Fibonacci Pullback System - FibonacciFlux', shorttitle = "AFPS", ...,
initial_capital = 10000, // Accessible capital
default_qty_type = strategy.percent_of_equity, // Equity-based risk
default_qty_value = 4, // Default 4% equity risk per initial trade
commission_type = strategy.commission.percent,
commission_value = 0.03, // Realistic commission
slippage = 2, // Realistic slippage
pyramiding = 2 // Limited pyramiding allowed
)
Note: The default 4% risk (`default_qty_value = 4`) requires careful user assessment and adjustment based on individual risk tolerance.
3.2. Historical Performance Insights & Institutional Potential:
Backtesting provides insights into historical behavior under specific conditions (always specify Asset/Timeframe/Dates when sharing results):
Default Performance Example: With defaults, historical tests might show characteristics like Overall PF ~1.38, Max DD ~1.16%, with potential Long/Short performance variance (e.g., Long PF 1.6+, Short PF < 1).
Optimized MTF Filter Performance: Crucially, historical simulations demonstrate that meticulous configuration of the MTF filters (particularly RSI and potentially others depending on market) can significantly enhance performance. Under specific, optimized MTF filter settings combined with appropriate risk management (e.g., 7.5% risk), historical tests have indicated the potential to achieve **Profit Factors exceeding 2.6**, alongside controlled drawdowns (e.g., ~1.32%). This level of performance, if consistently achievable (which requires ongoing adaptation), aligns with metrics often sought in institutional trading environments.
Disclaimer Reminder: These results are strictly historical simulations. Past performance does not guarantee future results. Achieving high performance requires careful parameter tuning, adaptation to changing markets, and robust risk management.
3.3. Emphasizing Risk Management:
Effective use of AFPS mandates active risk management. Utilize the built-in Stop Loss, Take Profit, and Trailing Stop features. The `pyramiding = 2` setting requires particularly diligent oversight. Do not rely solely on default settings.
4. Conclusion: Advancing Trend Pullback Strategies
The Adaptive Fibonacci Pullback System (AFPS) offers a sophisticated, theoretically grounded, and highly adaptable framework for identifying and executing high-probability trend pullback trades. Its unique blend of Fibonacci resonance, adaptive context, and multi-dimensional MTF filtering represents a significant advancement over conventional methods. While requiring thoughtful implementation and risk management, AFPS provides discerning traders with a powerful tool potentially capable of achieving institutional-level performance characteristics under optimized conditions.
Acknowledgments
Developed by FibonacciFlux. Inspired by principles of Fibonacci analysis, adaptive averaging, and multi-timeframe confirmation techniques explored within the trading community.
Disclaimer
Trading involves substantial risk. AFPS is an analytical tool, not a guarantee of profit. Past performance is not indicative of future results. Market conditions change. Users are solely responsible for their decisions and risk management. Thorough testing is essential. Deploy at your own considered risk.
Zig Zag Trend Metrics“ Zig Zag Trend Metrics ” is a highly versatile indicator, built on the classic Zig Zag concept and thoughtfully designed for technical traders seeking a deeper, more structured view of market dynamics. This tool identifies significant swing highs and lows, classifies them, and annotates each with key metrics, offering a precise snapshot of each movement. It enhances visual analysis by drawing connecting lines that outline the flow of market structure, making trend progression and reversals instantly recognizable. Beyond visual mapping, it features a compact, real-time statistics table that calculates the average price and time deltas for both bullish and bearish swings, giving traders deep insights into trend momentum and rhythm. With extensive customization options, this indicator adapts seamlessly to vast trading styles or chart setups, empowering traders to spot patterns, evaluate trend strength, and make more confident, data-backed decisions.
❖ FEATURES
✦ Automatic Swing Detection
At its core, this indicator automatically identifies swing highs and lows based on a customizable lookback period (default: 10 bars).
✦ Labeling Swing Points
Each swing is visualized with a label that includes:
Swing Classification : “HH” (Higher High), “LH” (Lower High), “LL” (Lower Low), or “HL” (Higher Low).
Price Difference : Displayed in percentage or absolute value from the previous opposite swing.
Time Difference : The number of bars since the previous swing of the opposite type.
These labels offer traders clear, immediate insight into price movements and structural changes.
✦ Visual Lines
The indicator draws three types of lines:
Bullish Lines: Connect recent swing lows to new swing highs, indicating uptrends.
Bearish Lines: Connect recent swing highs to new swing lows, indicating downtrends.
Range Lines: Connect consecutive highs or lows to outline price channels.
Each line type can be color-coded and customized for visibility.
✦ Statistics Table
An on-screen metrics table provides a live summary of trends. Script uses Relative Averaging to smooth price and time changes. This prevents outliers from distorting the data and provides a more reliable sense of typical swing behavior.
Uptrend Metrics: Shows average price and time differences from recent bullish swings.
Downtrend Metrics: Shows the same for bearish swings.
🛠️ Customization Options
Ability to tailor the indicator to suit their strategy and aesthetic preferences:
Swing Period: Adjust sensitivity to short- or long-term swings.
Color Settings: Customize line and label colors.
Label Display: Choose between absolute or percentage price differences.
Table Settings: Modify size, location, or visibility.
This makes the indicator highly flexible and useful across various timeframes and assets.
