LE LevelsGENERAL OVERVIEW:
The LE Levels indicator plots yesterday’s high/low and today’s pre-market high/low directly on your chart, then layers signal logic around those levels and a set of EMA waves. You can choose “Inside” setups, “Outside” setups, or both. You can also pick entries that trigger at levels, entries that trigger off the EMA wave, or both.
This indicator was developed by Flux Charts in collaboration with Ellis Dillinger (Ellydtrades).
What is the purpose of the indicator?:
The purpose of the LE Levels indicator is to give traders a clear view of how price is behaving around key session levels and EMA structure. It follows the same model EllyD teaches by showing where price is relative to the Previous Day High and Low and the Pre-Market High and Low, then printing signals when specific reactions occur around those levels.
What is the theory behind the indicator?:
The theory behind the LE Levels indicator is based on the concept of inside and outside days. An inside day occurs when price trades within the previous day’s high and low, signaling compression and potential breakout conditions. An outside day occurs when price moves beyond those boundaries, confirming expansion and directional bias. When price trades above the PDH or PMH, it reflects bullish control and potential continuation if supported by volume and momentum. When price trades below the PDL or PML, it shows bearish control and possible downside continuation. The idea is to combine this logic with tickers that have catalysts or news, since these events often bring higher-than-normal volume.
LE SCANNER FEATURES:
Key Levels
Signals
EMA Waves
Key Levels:
The LE Levels indicator automatically plots four key levels each day:
Previous Day High (PDH)
Previous Day Low (PDL)
Pre-Market High (PMH)
Pre-Market Low (PML)
🔹How are Key Levels used in the indicator?:
The key levels are a crucial factor in determining if the trend is bullish, bearish, or neutral trend bias. The indicator uses the key levels as a condition for identifying inside or outside setups (explained below). After determining a trend bias and setup type, the indicator prints long and short entry signals based on how price interacts with the key levels and 8 EMA Wave. (explained below).
These levels define where price previously reacted or reversed, helping traders visualize how current price action relates to prior session structure. They update automatically each day and pre-market session, allowing traders to see if price is trading inside, above, or below prior key ranges without manually drawing them.
Please Note: Pre-market times are based on U.S. market hours (Eastern Standard Time) and may vary for non-U.S. tickers or exchanges.
🔹Previous Day High (PDH):
The PDH marks the highest price reached during the previous regular trading session. It shows where buyers pushed price to its highest point before the market closed. This value is automatically pulled from the daily chart and projected forward onto intraday timeframes.
🔹Previous Day Low (PDL):
The PDL marks the lowest price reached during the previous regular trading session. It shows where selling pressure reached its lowest point before buyers stepped in. Like the PDH, this level is retrieved from the prior day’s data and extended into the current session.
🔹Pre-Market High (PMH):
The PMH is the highest price reached between 4:00 AM and 9:29 AM EST, before the regular market open. It shows how far buyers managed to push price up during the pre-market session.
🔹Pre-Market Low (PML):
The PML is the lowest price reached between 4:00 AM and 9:29 AM EST, before the regular market open. It shows how far sellers were able to drive price down during the pre-market session.
🔹Customization Options:
Extend Levels:
Extends each plotted line a user-defined number of bars into the future, keeping them visible even as new candles print. This helps maintain a clear visual reference as the session progresses.
Extend PDH/L Left & Extend PMH/L Left:
These settings let you extend the Previous Day and Pre-Market levels back to their origin point, so you can see exactly where each level was formed on the prior trading day. This makes it easy to understand the context of each level and how it developed. When this option is disabled, the lines begin at the regular session open instead of extending backward into the previous day’s data.
Show Name / Show Price:
Enabling Show Name displays labels (PDH, PDL, PMH, PML) beside each line, while Show Price adds the exact price value. You can choose to show just the name, just the price, or both for a complete label format.
Line Color and Style:
Each level can be fully customized. You can change the line color and select between solid, dashed, or dotted styles to visually distinguish each level type.
At the bottom of the indicator settings, under the ‘Miscellaneous’ section, two additional options allow further control over how levels are displayed:
Hide Previous Day Highs/Lows:
When enabled, the previous day’s high and low levels aren’t shown. When disabled, users can view previous day levels without using replay mode. By default, this setting is enabled.
Disabled:
Enabled:
Hide Previous Pre-Market Highs/Lows:
When enabled, the previous pre-market high and low levels aren’t shown. When disabled, users can view previous pre-market levels without using replay mode. By default, this setting is enabled.
Disabled:
Enabled:
Signals:
The LE Levels indicator automatically prints long and short entry signals based on how price interacts with its key levels (PDH, PDL, PMH, PML) and the EMA Waves. It identifies moments when price either breaks out beyond prior ranges or retests those levels in alignment with momentum shown by the EMA Waves.
There are two types of setups (Inside and Outside) and two entry types ((L)evels and (E)MAs). Together, these settings allow traders to customize the type of structure the indicator recognizes and how signals are generated.
🔹What is an Inside Setup?
An Inside Setup occurs when the current trading session forms entirely within the previous day’s range, meaning price has not yet broken above the Previous Day High (PDH) or below the Previous Day Low (PDL). In the LE Levels indicator, inside setups are recognized when price trades within the previous day’s boundaries while also considering the pre-market range (Pre-Market High and Pre-Market Low).
Inside Setups have two main conditions, depending on directional bias:
Bullish Inside Setup:
Price trades above the Pre-Market High (PMH) and above the Previous Day Low (PDL), while still below the Previous Day High (PDH).
Bearish Inside Setup:
Price trades below the Pre-Market Low (PML) and below the Previous Day High (PDH), while still above the Previous Day Low (PDL).
🔹What is an Outside Setup?
An Outside Setup occurs when the current trading session extends beyond the previous day’s range, meaning price has broken above the Previous Day High (PDH) or below the Previous Day Low (PDL). This structure reflects expansion and directional control, showing that either buyers or sellers have taken price into new territory beyond the prior session’s boundaries.
In the indicator, an Outside Setup forms once price closes beyond both the previous day and pre-market boundaries, showing bias in one direction.
Bullish Outside Setup:
Price closes above both the PDH and the PMH, confirming buyers have pushed through every key resistance from the prior session and the pre-market.
Bearish Outside Setup:
Price closes below both the PDL and the PML, showing sellers have pushed price beneath all key support levels from the previous session and the pre-market.
🔹Entry Types: (L)evels and (E)MAs
Once a setup type (Inside or Outside) has been established, the LE Levels indicator generates trade signals using one of two entry confirmation methods: (L) for Key Level based Entries and (E) for EMA Wave based Entries. These determine how the signal prints and what triggers it within.
🔹(L)evels Entry:
The (L)evels entry type is built around how price reacts to the key levels (PDH, PDL, PMH, PML). It prints when price retests those levels during an active setup. The logic focuses on retests, where price returns to confirm a previous breakout or breakdown before continuing in the same direction.
Bullish Outside (L)evels Setup:
A Bullish Outside Setup forms when price breaks above both the PDH and PMH. Once this breakout occurs, the indicator waits for a pullback to one of those levels. For a signal to print, the 8 EMA Wave must also be near that level, showing momentum is supporting the structure. A small buffer is applied between price and the level so that even if price only comes close, without fully touching, the retest still counts. When price holds above the PDH or PMH with the 8 EMA nearby, the indicator prints an (L) ▲ entry.
Bearish Outside (L)evels Setup:
A Bearish Outside Setup forms when price breaks below both the PDL and PML. Once this breakdown occurs, the indicator waits for a pullback to one of those levels. For a signal to print, the 8 EMA Wave must also be near that area, confirming momentum is aligned with the move. A small buffer is included so that even if price comes close but doesn’t fully touch the level, the retest still qualifies. When price holds below the PDL or PML with the 8 EMA nearby, the indicator prints an (L) ▼ entry.
Bullish Inside (L)evels Setup:
A Bullish Inside Setup forms when price trades above the PMH but stays below the PDH and above the PDL. Once this condition is met, the indicator waits for a pullback to the PMH. For a signal to print, the 8 EMA Wave must also be near that level. A small buffer is applied so that even if price only comes close to the level, the retest still counts. When price holds above the PMH with the 8 EMA nearby, the indicator prints an (L) ▲ entry.
Bearish Inside (L)evels Setup:
A Bearish Inside Setup forms when price trades below the PML but stays above the PDL and below the PDH. Once this condition is met, the indicator waits for a pullback to the PML. For a signal to print, the 8 EMA Wave must also be near that level. A small buffer is applied so that even if price only comes close, the retest still counts. When price holds below the PML with the 8 EMA nearby, the indicator prints an (L) ▼ entry.
🔹(E)MAs Entry:
The (E)MA Entry type focuses on how price reacts to the 8 EMA Wave. It identifies when price first interacts with the EMAs, then confirms continuation once momentum resumes in the setup’s direction. The first candle that touches the EMA prints an (E) marker, and the confirmation signal triggers only after price breaks above or below that candle, depending on the bias.
Bullish Outside (E)MA Setup:
A Bullish Outside Setup forms when price is trading above both the PDH and PMH. Once this breakout occurs, the indicator waits for price to pull back and touch the 8 EMA Wave, which prints the initial (E) label. If price then breaks above that candle’s high, the continuation setup is confirmed.
Bearish Outside (E)MA Setup:
A Bearish Outside Setup forms when price is trading below both the PDL and PML. After the breakdown, the indicator waits for price to pull back to the 8 EMA Wave, marking the candle that touches it with an (E) label. If price then breaks below that candle’s low, the continuation setup is confirmed.
Bullish Inside (E)MA Setup:
A Bullish Inside Setup forms when price trades above the PMH but remains below the PDH and above the PDL. The indicator waits for price to retrace and touch the 8 EMA Wave, which prints the initial (E) label. If price then breaks above that candle’s high, the continuation setup is confirmed.
Bearish Inside (E)MA Setup:
A Bearish Inside Setup forms when price trades below the PML but remains above the PDL and below the PDH. Once price touches the 8 EMA Wave, the indicator prints an (E) marker. If price then breaks below that candle’s low, the continuation setup is confirmed.
🔹Signal Settings:
At the bottom of the indicator settings panel, three core controls define how signals are displayed and which setups the indicator actively scans for. These settings allow you to refine signal generation based on your trading approach and chart preference.
Setup Type:
This setting determines which structural conditions the indicator tracks.
Inside Setups: Signals only appear when price is trading within the previous day’s range (between PDH and PDL).
Outside Setups: Signals only appear when price breaks outside the previous day’s range (above PDH/PMH or below PDL/PML).
Both: Enables signals for both Inside and Outside setups.
Entry Type:
Controls how the indicator confirms entries.
(E)MAs: Prints signals based on price interacting with the 8 EMA Wave.
(L)evels: Prints signals based on price retesting key levels such as PDH, PDL, PMH, or PML.
Both: Allows both EMA and Level-based signals to appear on the same chart.
Signal Filters (Long, Short, and Re-Entry):
These toggles let you control which trade directions are active.
Long: Displays only bullish entries and ignores all short setups.
Short: Displays only bearish entries and ignores long setups.
Re-Entry: Enables or disables repeated signals in the same direction after the first valid setup has printed. When off, only the initial signal is shown until conditions reset.
EMA Waves:
The EMA Waves help identify potential entries and show directional bias. They’re made of grouped EMAs that form shaded areas to create a “wave” look. The color-coding on the waves allows users to view when price is consolidating, in a bullish trend, or in a bearish trend. The wave updates in real time as new candles form and does not repaint historical data.
🔹8 EMA Wave
The 8 EMA Wave is used directly in the indicator’s signal logic described earlier. It reacts fastest to price compared to the other EAM Waves and determines when (L) and (E) signals can trigger.
How It Works:
The wave is made from the 8, 9, and 10 EMAs and fills the space between them to create a “wave” look. The 8 EMA Wave continuously updates its color based on where price trades relative to the key levels (PDH, PDL, PMH, PML). The color changes are conditional and based solely on price position relative to key levels.
Price is above both PDH and PMH: The wave is bright green, and the top half is purple.
Price is between PDH and PMH: The wave is dark green, and the top half is purple.
Price is below both PDL and PML: The wave is bright red, and the bottom half is purple.
Price is between PDL and PML: The wave is dark red, and the bottom half is purple.
Price is between all four levels: The wave is gray to represent consolidation or neutral bias.
🔹8 EMA Wave Signal Function:
For (L)evels entries, the 8 EMA must be close to the key level being retested, with a small buffer that allows near touches to qualify.
For (E)MA entries, the first candle that touches the wave prints an (E), and the confirmation signal appears when price breaks that candle’s high or low.
🔹8 EMA Wave Customization:
Users can customize all colors for bullish, bearish, and neutral conditions directly in the settings. The purple overlay color cannot be changed, as it is hard-coded into the indicator. The 8 EMA Wave can also be toggled on or off. Turning it off only removes the visual display from the chart and does not affect signals.
🔹20 EMA Wave
The 20 EMA Wave measures medium-term momentum and helps visualize larger pullbacks. It reacts more slowly than the 8 EMA Wave, giving a smoother wave look. No signals are generated from it. It’s purely a visual guide for spotting potential pullback areas for continuation setups.
How It Works:
The wave is made from the 19, 20, and 21 EMAs and fills the space between them to create a shaded “wave.” The color updates continuously based on where price trades relative to the key levels (PDH, PDL, PMH, PML). The color changes are conditional and based only on price position relative to these levels.
Price is above both PDH and PMH: The wave is bright green, and the top half is blue.
Price is between PDH and PMH: The wave is dark green, and the top half is blue.
Price is below both PDL and PML: The wave is bright red, and the bottom half is blue.
Price is between PDL and PML: The wave is dark red, and the bottom half is blue.
Price is between all four levels: The wave is gray to represent consolidation or neutral bias.
🔹20 EMA Wave Use Case:
After 12:00 PM EST, the 20 EMA Wave is used to spot larger pullbacks that form later in the session. No signals are generated from it; it only serves as a visual guide for identifying potential continuation areas.
Bullish Continuation Pullback:
Bearish Continuation Pullback:
🔹20 EMA Wave Customization:
Users can customize all colors for bullish, bearish, and neutral conditions directly in the settings. The blue overlay color cannot be changed, as it is hard-coded into the indicator. The 20 EMA Wave can also be toggled on or off.
🔹200 EMA Wave
The 200 EMA Wave is used to determine long-term trend bias. When price is above it, the bias is bullish; when price is below it, the bias is bearish. It updates automatically in real time and is used to define the broader directional bias for the day.
How it Works:
The 200 EMA Wave is created using the 190, 199, and 200 EMAs, with the area between them shaded to form a “wave.”
🔹200 EMA Wave Use Case:
When price is above the 200 EMA Wave and both the 8 and 20 EMA Waves are stacked above it, the overall trend is bullish.
When price is below the 200 EMA Wave and both shorter-term waves are also below it, the overall trend is bearish.
🔹200 EMA Wave Customization:
Users can customize both colors that form the 200 EMA Wave. The entire wave can also be toggled on or off in the settings.
Uniqueness:
The LE Levels indicator is unique because it combines signal logic with a clear visual structure. It automatically detects inside and outside setups, printing (L) and (E) entries based on how price reacts to key levels and the EMA Waves. Each signal follows strict conditions tied to the 8 EMA and key levels. The color-coded EMA Waves make it simple to understand where price is in relation to the key levels and getting a quick trend bias overview.
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VolumatrixVolumatrix is an enhanced volume weighted price indicator with advanced features
Created by CryptoJew & CryptoTiger on 04-06-2021
👋 Definition
Volumatrix turns current and historical price data into enhanced volume weighted price plots that allow you to visually grasp the momentum of any given market.
It’s easy to use and provides an accurate reading about an ongoing trend. This indicator is optimized to catch trend movements as soon as possible and to maximize certainty.
🙌 Overview
The Volumatrix indicator is based on an enhanced VWAP calculation, which serves as a present and upcoming price movement indication.
The further away the VWAP Wave is from the Zero Line, the more powerful the momentum is in that direction.
Conversely, the closer the VWAP Wave is to the Zero Line, the less momentum it has.
⭐️ Features
Volumatrix consists of the following features:
VWAP Waves: Visualizes the market's momentum in an easy-to-understand way by drawing colored waves.
VWAP Average: Acts as a calibration line for current wave movements.
Bearish & Bullish Dots: Indicates and confirms immediate trend changes by printing dual-colored dots.
E MA Backgrounds: Shows the general direction of the market, based on the exponential moving average (EMA).
In-depth alerts: Help traders discover potential trades with less time.
☝️ Basics
The Volume Weighted Average Price plays an essential role, as the Volumatrix indicator uses an enhanced VWAP calculation.
The volume weighted average price (VWAP) is a great technical trading indicator used by traders as it accounts for both price and volume.
VWAP signals the ratio of the cumulative share price to the cumulative volume traded over a given time.
It is essential because it provides traders with advanced insight into the trend and value of an asset.
Unlike moving averages, VWAP assigns more weight to price points with high volume.
This allows one to understand price points of interest, gauge relative strength, and identify prime entries/exits.
VWAP works with any interval: seconds, minutes, hours, days, weeks, months, years, etc...
However, keep in mind that VWAP can also experience some lag, much like a moving average.
Lag is inherent in the indicator because it's a calculation of an average using past data.
🧮 Calculation
Volume Weighted Average Price (VWAP) is constructed with two parameters, namely, price and volume, in 5 steps:
1. Calculate the Typical Price for the period.
((High + Low + Close)/3)
2. Multiply the Typical Price by the period Volume
(Typical Price x Volume)
3. Create a Cumulative Total of Typical Price
Cumulative(Typical Price x Volume)
4. Create a Cumulative Total of Volume
Cumulative(Volume)
5. Divide the Cumulative Totals
VWAP = Cumulative(Typical Price x Volume) / Cumulative(Volume)
🔍 Trend Identification - What to look for
VWAP is an excellent way to identify the trend of a market.
When using Volumatrix, you are looking for multiple confirmations that take place simultaneously.
The more confirmations that occur at the same time; the more certain the indicator will be.
You can identify the direction of a market by looking out for a few critical confirming signals.
📈 Bullish Trend Confirmations:
VWAP Wave overcrossing Zero Line :
When the VWAP Wave is crossing over the Zero Line, it indicates an immediate bullish trend.
This is one of the most certain moves that one can detect in Volumatrix.
This means that the price is about to change direction.
This is the case for any timeframe: seconds, minutes, hours, days, week, month, year, etc.
VWAP Wave color turning bullish:
When a bullish trend is about to happen, the VWAP Wave will change its color to yellow and finally to green.
That way, one can preemptively detect an upcoming bullish move.
In general, the VWAP Wave can change to 3 different colors.
Green means bullish.
Bullish Dots:
From time to time, bullish green dots will appear.
When combined with other indications, the Bullish Dots can be handy in confirming an upcoming or present uptrend.
That said, one should never solely rely on dots when deciding whether the trend is bullish or not.
Instead, if a trader sees a green dot, it should be taken as a hint to look for further bullish indications.
EMA Background:
One can identify the general trend of a market by looking at the background color of the indicator.
When the background is green, one can assume that a bullish trend is present.
The background color changes based on the exponential moving average (EMA).
By default, the 200 EMA is set. Change this value based on your timeframe preferences.
VWAP Average:
When the white VWAP Average line crosses above the Zero Line, it acts as an additional trend confirmation when combined with the VWAP waves.
As the VWAP average does not weigh in the short-term movements too heavily, it is less affected by immediate volatility.
Therefore, traders usually use the VWAP Average as a calibration tool to interpret the VWAP Waves more precisely.
📉 Bearish Trend Confirmations:
VWAP Wave under crossing Zero Line:
When the VWAP Wave is crossing under the Zero Line, it indicates an immediate bearish trend.
This is one of the most certain moves that one can detect in Volumatrix. This means that the price is about to change direction.
This is the case for any timeframe: seconds, minutes, hours, days, week, month, year, etc.
VWAP Wave turning bearish:
When a bearish trend is about to happen, the VWAP Wave will change its color to yellow and then finally to red.
That way, one can preemptively detect an upcoming bearish move. In general, the VWAP Wave can change to 3 different colors.
Red means bearish.
Bearish Dots:
From time to time, bearish red dots will appear.
When combined with other indications, the bearish dots can be handy in confirming an upcoming or present downtrend.
That said, one should never solely rely on dots when deciding whether the trend is bearish or not.
Instead, if a trader sees a red dot, it should be taken as a hint to look for further bearish indications.
EMA Background:
One can identify the general trend of a market by looking at the background color of the indicator.
When the background is red, one can assume that a bearish trend is present.
The background color changes based on the exponential moving average (EMA).
By default, the 200 EMA is set. Change this value based on your timeframe preferences.
VWAP Average:
When the white VWAP Average line crosses below the Zero Line, it acts as an additional trend confirmation if combined with the VWAP waves.
As the VWAP average does not weigh in the short-term movements too heavily, it is less affected by immediate volatility.
Therefore, traders usually use the VWAP Average as a calibration tool to interpret the VWAP Waves more precisely.
💤 Sideways Trend Confirmations:
VWAP Average:
When the VWAP Average is parallel and hovering around the Zero Line, either above or below it, that will indicate a sideways trend.
🚦 Usage - How and where to use it
The Volumatrix indicator is a universal indicator that works with any market capable of calculating a VWAP.
It’s currently being used in the following markets: cryptocurrency market, stock market, gold market and oil (just to name a few).
❗️ Requirements:
This indicator does not require any additional indicators as traders usually do in price action trading.
Basically, one just needs to follow the crossings, dots, and colors to get maximum certainty.
As a bonus, we recommend traders take advantage of TradingView’s multi-chart to catch more simultaneous confirmations.
🗣 Example Strategy: The 4 Timeframe Strategy
One can use the Volumatrix indicator along with the 4 timeframe strategy.
For example, open the 4 hour, 1 hour, 30 minute, and 5minute intervals simultaneously from left to right in a multi-chart layout.
Then lookout for the following conditions to meet:
OPEN LONG TRADE IF: On the 1-hour interval + 30-minute interval, Bullish Dots appear simultaneously
AND: On the 4-hour interval, the VWAP Wave is above the Zero Line
AND: On the 5-minute interval VWAP Wave is about to cross over the Zero Line or has already minimally crossed up.
OPEN SHORT TRADE IF: On the 1-hour interval + 30-minute interval, Bearish Dots appear simultaneously
AND: On the 4-hour interval VWAP Wave is below the Zero Line
AND: On the 5-minute interval VWAP Wave is about to cross under the Zero Line or has already minimally crossed down.
💡 Tips
Use TradingView’s 4-multi-chart layout to catch potential trades faster.
Use the indicator on a computer for optimal performance.
Set your computer screen to higher resolutions to get a better overview.
🔔 Alerts
With Volumatrix, you can use in-depth alerts like:
Bullish Dot
When a green dot at the bottom of the indicator appears
Bearish Dot
When a red dot at the bottom of the indicator appears
VWAP Wave Crossing Over Zero Line
When the VWAP Wave crosses over the Zero Line
VWAP Wave Crossing Under Zero Line
When the VWAP Wave crosses under the Zero Line
VWAP Wave Crossing Over Zero Line + Bullish Dot
When the VWAP Wave crosses over the Zero Line and a Bullish Dot appears
VWAP Wave Crossing Under Zero Line + Bearish Dot
When the VWAP Wave crosses over the Zero Line and a Bearish Dot appears
VWAP Average Crossing Over Zero Line
When the VWAP Average crosses over the Zero Line
VWAP Average Crossing Under Zero Line
When the VWAP Average crosses under the Zero Line
🔧 Settings
🔢 Inputs
These settings will change the behavior and outcome of the indicator.
EMA
Determines the number of previous candles that should be taken into calculation for the EMA background.
The value of the EMA can be changed to one's preferred value in accordance with the chosen interval.
The default value is 200.
🎨 Style
These settings will change the appearance of the indicator
VWAP Waves
Determines the color, opacity, thickness, and shape for the VWAP Waves.
The default shape is area.
The default colors are red, yellow & green.
VWAP Average
Determines the color, opacity, thickness, and shape for the VWAP Average.
The default shape is line.
The default color is white.
Zero Line
Determines the color, opacity, thickness, and shape for the Zero Line.
The default shape is a line.
The default color is white.
EMA Background
Determines the color & opacity for the Dynamic Background.
The default colors are black, red & green.
Bullish Dot
Determines the color, shape, opacity & location for the bullish dot.
The default shape is a circle.
The default color is green.
Bearish Dot
Determines the color, shape, opacity & location for the bearish dot.
The default shape is a circle.
The default color is red.
✅ Summary
Volumatrix is a unique indicator because, unlike many other VWAP tools, it's suited for simple as well as advanced analysis.
It’s a solid tool for immediately identifying the underlying trend of an asset.
Of course, this is true for any indicator based on the VWAP, which calculates an average using past data.
Still, Volumatrix is superior in this realm as it enhances the VWAP in its calculation and its visualization, while it comes with many advanced features.
❓ Questions
If you have any questions, just ask them here or in the Volumatrix community.
📚 Terminology
Bearish Dots: Red dots appearing at the bottom of the Volumatrix indicator.
Bullish Dots: Green dots appearing at the bottom of the Volumatrix indicator.
EMA: Exponential Moving Average - Tracks the price of an asset over time while giving more importance to recent price data.
Volume: A measure of how much of a given asset has traded in a period.
VWAP: Volume Weighted Average Price - The ratio of the value traded to total volume traded over time.
VWAP Average: Represents the average of the VWAP waves in the Volumatrix indicator.
VWAP Wave: The colorful waves representing the enhanced VWAP in the Volumatrix indicator.
Zero Line: It’s the indicator’s baseline and determines the beginning and end of a certain trend.
🙏 Acknowledgments
First, we would like to thank TradingView & PineCoders for this fantastic platform and technology.
We are also very grateful to our loyal trading community for constantly supporting our efforts.
We are looking forward to continuously improving this indicator for you.
Solar Movement Gradient-AYNETSummary of the Solar Movement Gradient Indicator
This Pine Script creates a dynamic, colorful indicator inspired by solar movements. It uses a sinusoidal wave to plot oscillations over time with a rainbow-like gradient that changes based on the wave's position.
Key Features
Sinusoidal Wave:
A wave oscillates smoothly based on the bar index (time) or optionally influenced by price movements.
The wave’s amplitude, baseline, and wavelength can be customized.
Dynamic Colors:
A spectrum of seven colors (red, orange, yellow, green, blue, purple, pink) is used.
The color changes smoothly along with the wave, emulating a solar gradient.
Background Gradient:
An optional gradient fills the background with colors matching the wave, adding a visually pleasing effect.
Customizable Inputs
Gradient Speed:
Adjusts how fast the wave and colors change over time.
Amplitude & Wavelength:
Controls the height and smoothness of the wave.
Price Influence:
Allows the wave to react dynamically to price movements.
Background Gradient:
Toggles a colorful gradient in the chart’s background.
Use Case
This indicator is designed for visual appeal rather than trading signals. It enhances the chart with a dynamic and colorful representation, making it perfect for aesthetic customization.
Let me know if you need further refinements! 🌈✨
Visual ProwessVisual Prowess: Ultimate Visual of Price Action Indicator
Overview
Visual Prowess is a Pine Script indicator that integrates Trend, Momentum, Strength/Weakness, Money Flow, and Volatility into a single, intuitive interface. Scaled from 0 to 100, it provides traders with clear bullish (>50) and bearish (<50) zones. Visual Prowess is made up of several data components which will be explained below. All these components have custom thresholds that lead to Green Dot Buy Signals and Red Dot sell signals. Designed for multi-timeframe analysis, it helps traders anticipate market moves with precision seeing behind the scenes of price action.
The fundamental inputs of price action are made up of different variables -- the components of Trend Strength, Volatility, Momentum, Money Flow/Volume and Overbought/Oversold. These are very important inputs market makers use. From what I've learned in my trading journey (always still learning), this is the data I value most important. This is why I combined all these components into one indicator.....to be an ultimate visual—this extrapolation of different pieces of data is the Visual Prowess.
What It Does
Visual Prowess combines five key market factors into a unified score (0-100) to assess market conditions by examining the price action like an x-ray aka Visual Prowess:
• Trend Direction & Strength (Green and Red Wave) : Identifies bullish (green clouds) or bearish (red clouds) trend. This data is designed to illustrate the trend by the color, and its strength by the height (score).
How it is Calculated = Data is derived from price action-- comparing the current and previous price highs and lows to measure the strength of upward (+) or downward (-) price movements, smoothed over a period and expressed as a percentage of the price range.
• Momentum (Blue and White Wave): Tracks price acceleration via a custom momentum oscillator, displayed as blue (positive) or white (negative) waves.
How it is Calculated = Data is calculated by subtracting a longer-term exponential moving average from a shorter-term exponential moving average to measure momentum and trend direction. Momentum strength is measured by height on 0-100 score, and color dictates the trend-- Blue up, White down.
• Strength Index (Purple Line): Measures overbought/oversold conditions with a normalized index, derived from price deviation.
How it is Calculated = Strength Index is calculated by comparing the average of price gains to the average of price losses over a specified period, expressed as a value between 0 and 100 to measure momentum and identify overbought or oversold conditions.
• Money Flow: Monitors capital inflows and outflows using a modified Money Flow Index, shown as green (buying) or red (selling) circles.
How it is Calculated = The Money Flow is calculated by using price and volume data to measure buying and selling pressure, comparing positive and negative money flow over a specified period to produce a value between 0 and 100, indicating overbought or oversold conditions and more importantly where the money is moving, + or -.
• Volatility: Gauges market volatility, marked by colored crosses (blue for low, red for high). Blue illustrates low volatility which is key for big moves either + or -; red to illustrate when price action is extremely overheated either + or -.
How it is Calculated = The volatility is calculated by the creator of the BBWP The_Caretaker. This excellent work is calculated using the width of the iconic indicator the Bollinger Bands (the difference between the upper and lower bands divided by the middle band (the moving average), expressed as a percentage to show how volatile the price is relative to its recent average.
Originality
Unlike traditional multi-indicator dashboards, Visual Prowess uses a combination of specific open-source indicators which I believe to be the most important inputs in price action-- trend, momentum, strength, money flow, and volatility into an all-in-one visual ratioed on a 0-100 scale. This unique synthesis of data reduces noise, prioritizes signal alignment, and a look behind the scenes of price action to see deeper into the movement – This combination of indicators has custom thresholds, when these components in alignment with each other hit certain parameters; it leads to key custom price action signals -- Green Dot Buy and Red Dot Sell signals.
There is also a bonus indicator….. a Yellow Triangle. When you see this, it is rare and strong. It only prints when strength index reaches extreme lows at the same time volatility reaches extreme highs…. It then waits to print the yellow triangle upon a third condition= which is price action is back in bullish/positive zone. This Yellow triangle is meant to be strong reversals of Macro Trend lows.
How to Use the Visual Prowess Components:
• Add to Chart: Apply Visual Prowess to any timeframe (recommended: higher timeframes 12H, 1D, 2D, 3D for optimal signals).
• Interpret Zones: Values >50 indicate bullish conditions (green background); <50 signal bearish conditions (red background).
Wait for Green Dot Buy signal for buys and Red Dot Sell signals for sells. One can read each component individually to gauge the price action and predict before the buy signal prints; all of those components merged together is what leads to the buy and sell signals. The story of what’s to come can be seen at lower timeframes before the higher timeframes print, that is a key way to gauge projections of bull or bear prints to come.
HOW TO READ EACH DATA COMPONENT
TREND CLOUDS: Green/red clouds show trend direction; vivid colors tied to number/ score on the 0-100 scale indicate strength of the trend.
Bull Conditions
Green cloud illustrates the trend is bullish. The height is correlated to the trend’s strength—this height is also aligned with colors, more transparent green is weak, then it gets more opaque being medium strength, and the most vibrant is the strongest. How to ride the bull condition is by seeing this transformation of trend get from weak to strong, until it tops out and the wave points down losing strength which alludes to the bear condition.
Bear Conditions
Vice versa with the bear condition. Different shades of red tie into the strength of the bear trend. How to read when things are about to get bearish, is by seeing bull trend shift levels of strength (Example- medium to weak). This transition of bull strength getting weaker is the start, once it gets to weak bear it has commenced until bearish strength tops out before it begins to get weaker leading to the next bull phase.
MOMENTUM WAVES: Blue waves above 50 suggest bullish momentum; white waves below 50 warn of bearish shifts.
Bull Conditions
Good to look at flips of white wave to blue in bearish zones to see the tide turning= guaranteed bullish when safely gets above and holds above 50 zone.
Bear Conditions
Vice versa for Bearish side of this momentum wave being blue wave turning white in bullish zone aiming down to break below 50 zone to confirm bearish descent.
STRENGTH INDEX: Values >80 indicate overbought; <20 suggest oversold. Look for “Bull” or “Bear” labels for divergences.
Bull Conditions
Above 50 level is key, so seeing price action break from below 50 to above 50 is strong buy condition until it gets overbought.
Bear Conditions
Once conditions are too overbought and falling making lower lows (especially when price action is climbing or staying sideways) it is indicating strength is getting weaker. When this indicator fights 50 level and breaks down below 50 level bearish conditions are coming until it gets to an oversold level.
MONEYFLOW: Green circles signal buying pressure; red circles indicate selling.
Bull Conditions
Green circles show money flow is positive so that’s a good sign of upward price action to come, and again above 50 level is bullish conditions
Bear Conditions
Red circles show money flow is negative so that’s a bad sign of price action to come, pointing down and breaking below 50 level is no good. It can have corrections in bullish scenario keep in mind seeing red doesn’t mean trend is over z9could be in higher low scenario).
VOLATILITY: Blue crosses (<25% volatility) suggest breakout potential; red crosses (>75%) warn of overheated markets.
Bull Conditions
This is a very important indication. Big volatile moves can move either direction + or -. When all other components look positive/bullish and this is signalling blue crosses it means a big move is coming and will most likely be in the upward direction –If all other components align/lean bullish.
Another bullish scenario is when price action is down large and red crosses are forming. This indicates that the downward move is overheated (red x’s are rare). This extremely oversold condition can be great buying opportunities when volatility is hot printing red x’s.
Bear Conditions
When all other components look negative/bearish and this is signalling blue crosses it means a big move is coming and will most likely be in the downward direction –If all other components align/lean bearish.
Another bearish scenario is when price action is up large and red crosses are forming. This indicates that the upward move is overheated (red x’s are rare). This extremely overbought condition can be great selling opportunities when volatility is hot printing red x’s.
*****All these components in alignment of hitting each pertaining important threshold--is what prints the green dot and sell signals to trade by. It is not black and white; each component has a sweet spot fine tuned to be triggered through analysis of what is happening individually to each component and how it is reacting to the price action data.
EXAMPLE= Taking a look at the screenshot (Perfect Scenario)
Bullish Examination
- Taking a look at the 2-D timeframe on BTC
x>50
x= all components traveling to the bullish zone. Blue wave, Strength Index with bullish divergence accumulation, Money Flow Positive with Green Trend Wave starting, with teal low volatility cross→→→ leads to Green Dot Buy Signal print…. And the big rise speaks for itself with price action and the big mountain wave of the Green Trend Wave.
This rise leads to
↓↓↓↓
Bearish Examination
Strength Index gets really high at 80 scale, Red X’s showing extremely heated Volatility, Money Flow turning red and sloping down, Trend Wave peaking starting to roll over, Blue Momentum Wave transitioning to white, bearish divergence of price action related to Strength Index→→→ leads to Red Dot Sell Signal print… and the flush speaks for itself when all components fall below 50 level with Trend wave turning red
All this is forecasted in the data, showing weakness before weakness and showing strength before strength. It works because every single piece of important elements in data of price action is incorporated in this all-in-one indicator…. Which leads to the reasoning of me calling this indicator the Visual Prowess, for its unprecedent sharpness of visual observation.
****This is a passion script incorporating every piece of data I value important when reading a chart — to see current perspective of a chart and to help foresee future projection of direction Up or Down. Any community feedback is greatly appreciated. Ongoing work will be done on this script as new thoughts and fine tuning will continuously be done for infinity, as this is my personal go to model for data on the markets.
Awesome Oscillator (AO) with Signals [AIBitcoinTrend]👽 Multi-Scale Awesome Oscillator (AO) with Signals (AIBitcoinTrend)
The Multi-Scale Awesome Oscillator transforms the traditional Awesome Oscillator (AO) by integrating multi-scale wavelet filtering, enhancing its ability to detect momentum shifts while maintaining responsiveness across different market conditions.
Unlike conventional AO calculations, this advanced version refines trend structures using high-frequency, medium-frequency, and low-frequency wavelet components, providing traders with superior clarity and adaptability.
Additionally, it features real-time divergence detection and an ATR-based dynamic trailing stop, making it a powerful tool for momentum analysis, reversals, and breakout strategies.
👽 What Makes the Multi-Scale AO – Wavelet-Enhanced Momentum Unique?
Unlike traditional AO indicators, this enhanced version leverages wavelet-based decomposition and volatility-adjusted normalization, ensuring improved signal consistency across various timeframes and assets.
✅ Wavelet Smoothing – Multi-Scale Extraction – Captures short-term fluctuations while preserving broader trend structures.
✅ Frequency-Based Detail Weights – Separates high, medium, and low-frequency components to reduce noise and improve trend clarity.
✅ Real-Time Divergence Detection – Identifies bullish and bearish divergences for early trend reversals.
✅ Crossovers & ATR-Based Trailing Stops – Implements intelligent trade management with adaptive stop-loss levels.
👽 The Math Behind the Indicator
👾 Wavelet-Based AO Smoothing
The indicator applies multi-scale wavelet decomposition to extract high-frequency, medium-frequency, and low-frequency trend components, ensuring an optimal balance between reactivity and smoothness.
sma1 = ta.sma(signal, waveletPeriod1)
sma2 = ta.sma(signal, waveletPeriod2)
sma3 = ta.sma(signal, waveletPeriod3)
detail1 = signal - sma1 // High-frequency detail
detail2 = sma1 - sma2 // Intermediate detail
detail3 = sma2 - sma3 // Low-frequency detail
advancedAO = weightDetail1 * detail1 + weightDetail2 * detail2 + weightDetail3 * detail3
Why It Works:
Short-Term Smoothing: Captures rapid fluctuations while minimizing noise.
Medium-Term Smoothing: Balances short-term and long-term trends.
Long-Term Smoothing: Enhances trend stability and reduces false signals.
👾 Z-Score Normalization
To ensure consistency across different markets, the Awesome Oscillator is normalized using a Z-score transformation, making overbought and oversold levels stable across all assets.
normFactor = ta.stdev(advancedAO, normPeriod)
normalizedAO = advancedAO / nz(normFactor, 1)
Why It Works:
Standardizes AO values for comparison across assets.
Enhances signal reliability, preventing misleading spikes.
👽 How Traders Can Use This Indicator
👾 Divergence Trading Strategy
Bullish Divergence
Price makes a lower low, while AO forms a higher low.
A buy signal is confirmed when AO starts rising.
Bearish Divergence
Price makes a higher high, while AO forms a lower high.
A sell signal is confirmed when AO starts declining.
👾 Buy & Sell Signals with Trailing Stop
Bullish Setup:
✅AO crosses above the bullish trigger level → Buy Signal.
✅Trailing stop placed at Low - (ATR × Multiplier).
✅Exit if price crosses below the stop.
Bearish Setup:
✅AO crosses below the bearish trigger level → Sell Signal.
✅Trailing stop placed at High + (ATR × Multiplier).
✅Exit if price crosses above the stop.
👽 Why It’s Useful for Traders
Wavelet-Enhanced Filtering – Retains essential trend details while eliminating excessive noise.
Multi-Scale Momentum Analysis – Separates different trend frequencies for enhanced clarity.
Real-Time Divergence Alerts – Identifies early reversal signals for better entries and exits.
ATR-Based Risk Management – Ensures stops dynamically adapt to market conditions.
Works Across Markets & Timeframes – Suitable for stocks, forex, crypto, and futures trading.
👽 Indicator Settings
AO Short Period – Defines the short-term moving average for AO calculation.
AO Long Period – Defines the long-term moving average for AO smoothing.
Wavelet Smoothing – Adjusts multi-scale decomposition for different market conditions.
Divergence Detection – Enables or disables real-time divergence analysis. Normalization Period – Sets the lookback period for standard deviation-based AO normalization.
Cross Signals Sensitivity – Controls crossover signal strength for buy/sell signals.
ATR Trailing Stop Multiplier – Adjusts the sensitivity of the trailing stop.
Disclaimer: This indicator is designed for educational purposes and does not constitute financial advice. Please consult a qualified financial advisor before making investment decisions.
Stochastic Zone Strength Trend [wbburgin](This script was originally invite-only, but I'd vastly prefer contributing to the TradingView community more than anything else, so I am making it public :) I'd much rather share my ideas with you all.)
The Stochastic Zone Strength Trend indicator is a very powerful momentum and trend indicator that 1) identifies trend direction and strength, 2) determines pullbacks and reversals (including oversold and overbought conditions), 3) identifies divergences, and 4) can filter out ranges. I have some examples below on how to use it to its full effectiveness. It is composed of two components: Stochastic Zone Strength and Stochastic Trend Strength.
Stochastic Zone Strength
At its most basic level, the stochastic Zone Strength plots the momentum of the price action of the instrument, and identifies bearish and bullish changes with a high degree of accuracy. Think of the stochastic Zone Strength as a much more robust equivalent of the RSI. Momentum-change thresholds are demonstrated by the "20" and "80" levels on the indicator (see below image).
Stochastic Trend Strength
The stochastic Trend Strength component of the script uses resistance in each candlestick to calculate the trend strength of the instrument. I'll go more into detail about the settings after my description of how to use the indicator, but there are two forms of the stochastic Trend Strength:
Anchored at 50 (directional stochastic Trend Strength):
The directional stochastic Trend Strength can be used similarly to the MACD difference or other histogram-like indicators : a rising plot indicates an upward trend, while a falling plot indicates a downward trend.
Anchored at 0 (nondirectional stochastic Trend Strength):
The nondirectional stochastic Trend Strength can be used similarly to the ADX or other non-directional indicators : a rising plot indicates increasing trend strength, and look at the stochastic Zone Strength component and your instrument to determine if this indicates increasing bullish strength or increasing bearish strength (see photo below):
(In the above photo, a bearish divergence indicated that the high Trend Strength predicted a strong downwards move, which was confirmed shortly after. Later, a bullish move upward by the Zone Strength while the Trend Strength was elevated predicated a strong upwards move, which was also confirmed. Note the period where the Trend Strength never reached above 80, which indicated a ranging period (and thus unprofitable to enter or exit)).
How to Use the Indicator
The above image is a good example on how to use the indicator to determine divergences and possible pivot points (lines and circles, respectively). I recommend using both the stochastic Zone Strength and the stochastic Trend Strength at the same time, as it can give you a robust picture of where momentum is in relation to the price action and its trajectory. Every color is changeable in the settings.
Settings
The Amplitude of the indicator is essentially the high-low lookback for both components.
The Wavelength of the indicator is how stretched-out you want the indicator to be: how many amplitudes do you want the indicator to process in one given bar.
A useful analogy that I use (and that I derived the names from) is from traditional physics. In wave motion, the Amplitude is the up-down sensitivity of the wave, and the Wavelength is the side-side stretch of the wave.
The Smoothing Factor of the settings is simply how smoothed you want the stochastic to be. It's not that important in most circumstances.
Trend Anchor was covered above (see my description of Trend Strength). The "Trend Transform MA Length" is the EMA length of the Trend Strength that you use to transform it into the directional oscillator. Think of the EMA being transformed onto the 50 line and then the Trend Strength being dragged relative to that.
Trend Transform MA Length is the EMA length you want to use for transforming the nondirectional Trend Strength (anchored at 0) into the directional Trend Strength (anchored at 50). I suggest this be the same as the wavelength.
Trend Plot Type can transform the Nondirectional Trend Strength into a line plot so that it doesn't murk up the background.
Finally, the colors are changeable on the bottom.
Explanation of Zone Strength
If you're knowledgeable in Pine Script, I encourage you to look at the code to try to understand the concept, as it's a little complicated. The theory behind my Zone Strength concept is that the wicks in every bar can be used create an index of bullish and bearish resistance, as a wick signifies that the price crossed above a threshold before returning to its origin. This distance metric is unique because most indicators/formulas for calculating relative strength use a displacement metric (such as close - open) instead of measuring how far the price actually moved (up and down) within a candlestick. This is what the Zone Strength concept represents - the hesitation within the bar that is not typically represented in typical momentum indicators.
In the script's code I have step by step explanations of how the formula is calculated and why it is calculated as such. I encourage you to play around with the amplitude and wavelength inputs as they can make the zone strength look very different and perform differently depending on your interests.
Enjoy!
Walker
MFx Radar (Money Flow x-Radar)Description:
MFx Radar is a precision-built multi-timeframe analysis tool designed to identify high-probability trend shifts and accumulation/distribution events using a combination of WaveTrend dynamics, normalized money flow, RSI, BBWP, and OBV-based trend biasing.
Multi-Timeframe Trend Scanner
Analyze trend direction across 5 customizable timeframes using WaveTrend logic to produce a clear trend consensus.
Smart Money Flow Detection
Adaptive hybrid money flow combines CMF and MFI, normalized across lookback periods, to pinpoint shifts in accumulation or distribution with high sensitivity.
Event-Based Labels & Alerts
Minimalist "Accum" and "Distr" text labels appear at key inflection points, based on hybrid flow flips — designed to highlight smart money moves without clutter.
Trigger & Pattern Recognition
Built-in logic detects anchor points, trigger confirmations, and rare "Snake Eye" formations directly on WaveTrend, enhancing trade timing accuracy.
Visual Dashboard Table
A real-time table provides score-based insight into signal quality, trend direction, and volume behavior, giving you a full picture at a glance.
MFx Radar helps streamline discretionary and system-based trading decisions by surfacing key confluences across price, volume, and momentum all while staying out of your way visually.
How to Use MFx Radar
MFx Radar is a multi-timeframe market intelligence tool designed to help you spot trend direction, momentum shifts, volume strength, and high-probability trade setups using confluence across price, flow, and timeframes.
Where to find settings To see the full visual setup:
After adding the script, open the Settings gear. Go to the Inputs tab and enable:
Show Trigger Diamonds
Show WT Cross Circles
Show Anchor/Trigger/Snake Eye Labels
Show Table
Show OBV Divergence
Show Multi-TF Confluence
Show Signal Score
Then, go to the Style tab to adjust colors and fills for the wave plots and hybrid money flow. (Use published chart as a reference.)
What the Waves and Colors Mean
Blue WaveTrend (WT1 / WT2). These are the main momentum waves.
WT1 > WT2 = bullish momentum
WT1 < WT2 = bearish momentum
Above zero = bullish bias
Below zero = bearish bias
When WT1 crosses above WT2, it often marks the beginning of a move — these are shown as green trigger diamonds.
VWAP-MACD Line
The yellow fill helps spot volume-based momentum.
Rising = trend acceleration
Use together with BBWP (bollinger band width percentile) and hybrid money flow for confirmation.
Hybrid Money Flow
Combines CMF and MFI, normalized and smoothed.
Green = accumulation
Red = distribution
Transitions are key — especially when price moves up, but money flow stays red (a divergence warning).
This is useful for spotting fakeouts or confirming smart money shifts.
Orange Vertical Highlights
Shows when price is rising, but money flow is still red.
Often a sign of hidden distribution or "exit pump" behavior.
Table Dashboard (Bottom-Right)
BBWP (Volatility Pulse)
When BBWP is low (<20), it signals consolidation — a breakout is likely to follow.
Use this with ADX and WaveTrend position to anticipate directional breakouts.
Trend by ADX
Shows whether the market is trending and in which direction.
Combined with money flow and RSI, this gives strong confirmation on breakouts.
OBV HTF Bias
Gives higher timeframe pressure (bullish/bearish/neutral).
Helps avoid taking counter-trend trades.
Pattern Labels (WT-Based)
A = Anchor Wave — WT hitting oversold
T = Trigger Wave — WT turning back up after anchor
👀 = Snake Eyes — Rare pattern, usually signaling strong reversal potential
These help in timing entries, especially when they align with other signals like BBWP breakouts, confluence, or smart money flow flips.
Multi-Timeframe (MTF) Consensus
The system checks WaveTrend on 5 different timeframes and gives:
Color-coded signals on each TF
A final score: “Mostly Up,” “Mostly Down,” or “Mixed”
When MTFs align with wave crosses, BBWP expansion, and hybrid money flow shifts, the probability of sustained move is higher.
Divergence Spotting (Advanced Tip)
Watch for:Price rising while money flow is red → Possible trap / early exit
Price dropping while money flow is green → Early accumulation
Combine this with anchor-trigger patterns and MTF trend support for spotting bottoms or tops early.
Final Tips
Use WT trigger crosses as initial signal. Confirm with money flow direction + color flip
Look at BBWP for breakout timing. Use table as your decision dashboard
Favor trades that align with MTF consensus
TASC 2025.06 Cybernetic Oscillator█ OVERVIEW
This script implements the Cybernetic Oscillator introduced by John F. Ehlers in his article "The Cybernetic Oscillator For More Flexibility, Making A Better Oscillator" from the June 2025 edition of the TASC Traders' Tips . It cascades two-pole highpass and lowpass filters, then scales the result by its root mean square (RMS) to create a flexible normalized oscillator that responds to a customizable frequency range for different trading styles.
█ CONCEPTS
Oscillators are indicators widely used by technical traders. These indicators swing above and below a center value, emphasizing cyclic movements within a frequency range. In his article, Ehlers explains that all oscillators share a common characteristic: their calculations involve computing differences . The reliance on differences is what causes these indicators to oscillate about a central point.
The difference between two data points in a series acts as a highpass filter — it allows high frequencies (short wavelengths) to pass through while significantly attenuating low frequencies (long wavelengths). Ehlers demonstrates that a simple difference calculation attenuates lower-frequency cycles at a rate of 6 dB per octave. However, the difference also significantly amplifies cycles near the shortest observable wavelength, making the result appear noisier than the original series. To mitigate the effects of noise in a differenced series, oscillators typically smooth the series with a lowpass filter, such as a moving average.
Ehlers highlights an underlying issue with smoothing differenced data to create oscillators. He postulates that market data statistically follows a pink spectrum , where the amplitudes of cyclic components in the data are approximately directly proportional to the underlying periods. Specifically, he suggests that cyclic amplitude increases by 6 dB per octave of wavelength.
Because some conventional oscillators, such as RSI, use differencing calculations that attenuate cycles by only 6 dB per octave, and market cycles increase in amplitude by 6 dB per octave, such calculations do not have a tangible net effect on larger wavelengths in the analyzed data. The influence of larger wavelengths can be especially problematic when using these oscillators for mean reversion or swing signals. For instance, an expected reversion to the mean might be erroneous because oscillator's mean might significantly deviate from its center over time.
To address the issues with conventional oscillator responses, Ehlers created a new indicator dubbed the Cybernetic Oscillator. It uses a simple combination of highpass and lowpass filters to emphasize a specific range of frequencies in the market data, then normalizes the result based on RMS. The process is as follows:
Apply a two-pole highpass filter to the data. This filter's critical period defines the longest wavelength in the oscillator's passband.
Apply a two-pole SuperSmoother (lowpass filter) to the highpass-filtered data. This filter's critical period defines the shortest wavelength in the passband.
Scale the resulting waveform by its RMS. If the filtered waveform follows a normal distribution, the scaled result represents amplitude in standard deviations.
The oscillator's two-pole filters attenuate cycles outside the desired frequency range by 12 dB per octave. This rate outweighs the apparent rate of amplitude increase for successively longer market cycles (6 dB per octave). Therefore, the Cybernetic Oscillator provides a more robust isolation of cyclic content than conventional oscillators. Best of all, traders can set the periods of the highpass and lowpass filters separately, enabling fine-tuning of the frequency range for different trading styles.
█ USAGE
The "Highpass period" input in the "Settings/Inputs" tab specifies the longest wavelength in the oscillator's passband, and the "Lowpass period" input defines the shortest wavelength. The oscillator becomes more responsive to rapid movements with a smaller lowpass period. Conversely, it becomes more sensitive to trends with a larger highpass period. Ehlers recommends setting the smallest period to a value above 8 to avoid aliasing. The highpass period must not be smaller than the lowpass period. Otherwise, it causes a runtime error.
The "RMS length" input determines the number of bars in the RMS calculation that the indicator uses to normalize the filtered result.
This indicator also features two distinct display styles, which users can toggle with the "Display style" input. With the "Trend" style enabled, the indicator plots the oscillator with one of two colors based on whether its value is above or below zero. With the "Threshold" style enabled, it plots the oscillator as a gray line and highlights overbought and oversold areas based on the user-specified threshold.
Below, we show two instances of the script with different settings on an equities chart. The first uses the "Threshold" style with default settings to pass cycles between 20 and 30 bars for mean reversion signals. The second uses a larger highpass period of 250 bars and the "Trend" style to visualize trends based on cycles spanning less than one year:
Infinity Market Grid -AynetConcept
Imagine viewing the market as a dynamic grid where price, time, and momentum intersect to reveal infinite possibilities. This indicator leverages:
Grid-Based Market Flow: Visualizes price action as a grid with zones for:
Accumulation
Distribution
Breakout Expansion
Volatility Compression
Predictive Dynamic Layers:
Forecasts future price zones using historical volatility and momentum.
Tracks event probabilities like breakout, fakeout, and trend reversals.
Data Science Visuals:
Uses heatmap-style layers, moving waveforms, and price trajectory paths.
Interactive Alerts:
Real-time alerts for high-probability market events.
Marks critical zones for "buy," "sell," or "wait."
Key Features
Market Layers Grid:
Creates dynamic "boxes" around price using fractals and ATR-based volatility.
These boxes show potential future price zones and probabilities.
Volatility and Momentum Waves:
Overlay volatility oscillators and momentum bands for directional context.
Dynamic Heatmap Zones:
Colors the chart dynamically based on breakout probabilities and risk.
Price Path Prediction:
Tracks price trajectory as a moving "wave" across the grid.
How It Works
Grid Box Structure:
Upper and lower price levels are based on ATR (volatility) and plotted dynamically.
Dashed green/red lines show the grid for potential price expansion zones.
Heatmap Zones:
Colors the background based on probabilities:
Green: High breakout probability.
Blue: High consolidation probability.
Price Path Prediction:
Forecasts future price movements using momentum.
Plots these as a dynamic "wave" on the chart.
Momentum and Volatility Waves:
Shows the relationship between momentum and volatility as oscillating waves.
Helps identify when momentum exceeds volatility (potential breakouts).
Buy/Sell Signals:
Triggers when price approaches grid edges with strong momentum.
Provides alerts and visual markers.
Why Is It Revolutionary?
Grid and Wave Synergy:
Combines structural price zones (grid boxes) with real-time momentum and volatility waves.
Predictive Analytics:
Uses momentum-based forecasting to visualize what’s next, not just what’s happening.
Dynamic Heatmap:
Creates a living map of breakout/consolidation zones in real-time.
Scalable for Any Market:
Works seamlessly with forex, crypto, and stocks by adjusting the ATR multiplier and box length.
This indicator is not just a tool but a framework for understanding market dynamics at a deeper level. Let me know if you'd like to take it even further — for example, adding machine learning-inspired probability models or multi-timeframe analysis! 🚀
Aetherium Institutional Market Resonance EngineAetherium Institutional Market Resonance Engine (AIMRE)
A Three-Pillar Framework for Decoding Institutional Activity
🎓 THEORETICAL FOUNDATION
The Aetherium Institutional Market Resonance Engine (AIMRE) is a multi-faceted analysis system designed to move beyond conventional indicators and decode the market's underlying structure as dictated by institutional capital flow. Its philosophy is built on a singular premise: significant market moves are preceded by a convergence of context , location , and timing . Aetherium quantifies these three dimensions through a revolutionary three-pillar architecture.
This system is not a simple combination of indicators; it is an integrated engine where each pillar's analysis feeds into a central logic core. A signal is only generated when all three pillars achieve a state of resonance, indicating a high-probability alignment between market organization, key liquidity levels, and cyclical momentum.
⚡ THE THREE-PILLAR ARCHITECTURE
1. 🌌 PILLAR I: THE COHERENCE ENGINE (THE 'CONTEXT')
Purpose: To measure the degree of organization within the market. This pillar answers the question: " Is the market acting with a unified purpose, or is it chaotic and random? "
Conceptual Framework: Institutional campaigns (accumulation or distribution) create a non-random, organized market environment. Retail-driven or directionless markets are characterized by "noise" and chaos. The Coherence Engine acts as a filter to ensure we only engage when institutional players are actively steering the market.
Formulaic Concept:
Coherence = f(Dominance, Synchronization)
Dominance Factor: Calculates the absolute difference between smoothed buying pressure (volume-weighted bullish candles) and smoothed selling pressure (volume-weighted bearish candles), normalized by total pressure. A high value signifies a clear winner between buyers and sellers.
Synchronization Factor: Measures the correlation between the streams of buying and selling pressure over the analysis window. A high positive correlation indicates synchronized, directional activity, while a negative correlation suggests choppy, conflicting action.
The final Coherence score (0-100) represents the percentage of market organization. A high score is a prerequisite for any signal, filtering out unpredictable market conditions.
2. 💎 PILLAR II: HARMONIC LIQUIDITY MATRIX (THE 'LOCATION')
Purpose: To identify and map high-impact institutional footprints. This pillar answers the question: " Where have institutions previously committed significant capital? "
Conceptual Framework: Large institutional orders leave indelible marks on the market in the form of anomalous volume spikes at specific price levels. These are not random occurrences but are areas of intense historical interest. The Harmonic Liquidity Matrix finds these footprints and consolidates them into actionable support and resistance zones called "Harmonic Nodes."
Algorithmic Process:
Footprint Identification: The engine scans the historical lookback period for candles where volume > average_volume * Institutional_Volume_Filter. This identifies statistically significant volume events.
Node Creation: A raw node is created at the mean price of the identified candle.
Dynamic Clustering: The engine uses an ATR-based proximity algorithm. If a new footprint is identified within Node_Clustering_Distance (ATR) of an existing Harmonic Node, it is merged. The node's price is volume-weighted, and its magnitude is increased. This prevents chart clutter and consolidates nearby institutional orders into a single, more significant level.
Node Decay: Nodes that are older than the Institutional_Liquidity_Scanback period are automatically removed from the chart, ensuring the analysis remains relevant to recent market dynamics.
3. 🌊 PILLAR III: CYCLICAL RESONANCE MATRIX (THE 'TIMING')
Purpose: To identify the market's dominant rhythm and its current phase. This pillar answers the question: " Is the market's immediate energy flowing up or down? "
Conceptual Framework: Markets move in waves and cycles of varying lengths. Trading in harmony with the current cyclical phase dramatically increases the probability of success. Aetherium employs a simplified wavelet analysis concept to decompose price action into short, medium, and long-term cycles.
Algorithmic Process:
Cycle Decomposition: The engine calculates three oscillators based on the difference between pairs of Exponential Moving Averages (e.g., EMA8-EMA13 for short cycle, EMA21-EMA34 for medium cycle).
Energy Measurement: The 'energy' of each cycle is determined by its recent volatility (standard deviation). The cycle with the highest energy is designated as the "Dominant Cycle."
Phase Analysis: The engine determines if the dominant cycles are in a bullish phase (rising from a trough) or a bearish phase (falling from a peak).
Cycle Sync: The highest conviction timing signals occur when multiple cycles (e.g., short and medium) are synchronized in the same direction, indicating broad-based momentum.
🔧 COMPREHENSIVE INPUT SYSTEM
Pillar I: Market Coherence Engine
Coherence Analysis Window (10-50, Default: 21): The lookback period for the Coherence Engine.
Lower Values (10-15): Highly responsive to rapid shifts in market control. Ideal for scalping but can be sensitive to noise.
Balanced (20-30): Excellent for day trading, capturing the ebb and flow of institutional sessions.
Higher Values (35-50): Smoother, more stable reading. Best for swing trading and identifying long-term institutional campaigns.
Coherence Activation Level (50-90%, Default: 70%): The minimum market organization required to enable signal generation.
Strict (80-90%): Only allows signals in extremely clear, powerful trends. Fewer, but potentially higher quality signals.
Standard (65-75%): A robust filter that effectively removes choppy conditions while capturing most valid institutional moves.
Lenient (50-60%): Allows signals in less-organized markets. Can be useful in ranging markets but may increase false signals.
Pillar II: Harmonic Liquidity Matrix
Institutional Liquidity Scanback (100-400, Default: 200): How far back the engine looks for institutional footprints.
Short (100-150): Focuses on recent institutional activity, providing highly relevant, immediate levels.
Long (300-400): Identifies major, long-term structural levels. These nodes are often extremely powerful but may be less frequent.
Institutional Volume Filter (1.3-3.0, Default: 1.8): The multiplier for detecting a volume spike.
High (2.5-3.0): Only registers climactic, undeniable institutional volume. Fewer, but more significant nodes.
Low (1.3-1.7): More sensitive, identifying smaller but still relevant institutional interest.
Node Clustering Distance (0.2-0.8 ATR, Default: 0.4): The ATR-based distance for merging nearby nodes.
High (0.6-0.8): Creates wider, more consolidated zones of liquidity.
Low (0.2-0.3): Creates more numerous, precise, and distinct levels.
Pillar III: Cyclical Resonance Matrix
Cycle Resonance Analysis (30-100, Default: 50): The lookback for determining cycle energy and dominance.
Short (30-40): Tunes the engine to faster, shorter-term market rhythms. Best for scalping.
Long (70-100): Aligns the timing component with the larger primary trend. Best for swing trading.
Institutional Signal Architecture
Signal Quality Mode (Professional, Elite, Supreme): Controls the strictness of the three-pillar confluence.
Professional: Loosest setting. May generate signals if two of the three pillars are in strong alignment. Increases signal frequency.
Elite: Balanced setting. Requires a clear, unambiguous resonance of all three pillars. The recommended default.
Supreme: Most stringent. Requires perfect alignment of all three pillars, with each pillar exhibiting exceptionally strong readings (e.g., coherence > 85%). The highest conviction signals.
Signal Spacing Control (5-25, Default: 10): The minimum bars between signals to prevent clutter and redundant alerts.
🎨 ADVANCED VISUAL SYSTEM
The visual architecture of Aetherium is designed not merely for aesthetics, but to provide an intuitive, at-a-glance understanding of the complex data being processed.
Harmonic Liquidity Nodes: The core visual element. Displayed as multi-layered, semi-transparent horizontal boxes.
Magnitude Visualization: The height and opacity of a node's "glow" are proportional to its volume magnitude. More significant nodes appear brighter and larger, instantly drawing the eye to key levels.
Color Coding: Standard nodes are blue/purple, while exceptionally high-magnitude nodes are highlighted in an accent color to denote critical importance.
🌌 Quantum Resonance Field: A dynamic background gradient that visualizes the overall market environment.
Color: Shifts from cool blues/purples (low coherence) to energetic greens/cyans (high coherence and organization), providing instant context.
Intensity: The brightness and opacity of the field are influenced by total market energy (a composite of coherence, momentum, and volume), making powerful market states visually apparent.
💎 Crystalline Lattice Matrix: A geometric web of lines projected from a central moving average.
Mathematical Basis: Levels are projected using multiples of the Golden Ratio (Phi ≈ 1.618) and the ATR. This visualizes the natural harmonic and fractal structure of the market. It is not arbitrary but is based on mathematical principles of market geometry.
🧠 Synaptic Flow Network: A dynamic particle system visualizing the engine's "thought process."
Node Density & Activation: The number of particles and their brightness/color are tied directly to the Market Coherence score. In high-coherence states, the network becomes a dense, bright, and organized web. In chaotic states, it becomes sparse and dim.
⚡ Institutional Energy Waves: Flowing sine waves that visualize market volatility and rhythm.
Amplitude & Speed: The height and speed of the waves are directly influenced by the ATR and volume, providing a feel for market energy.
📊 INSTITUTIONAL CONTROL MATRIX (DASHBOARD)
The dashboard is the central command console, providing a real-time, quantitative summary of each pillar's status.
Header: Displays the script title and version.
Coherence Engine Section:
State: Displays a qualitative assessment of market organization: ◉ PHASE LOCK (High Coherence), ◎ ORGANIZING (Moderate Coherence), or ○ CHAOTIC (Low Coherence). Color-coded for immediate recognition.
Power: Shows the precise Coherence percentage and a directional arrow (↗ or ↘) indicating if organization is increasing or decreasing.
Liquidity Matrix Section:
Nodes: Displays the total number of active Harmonic Liquidity Nodes currently being tracked.
Target: Shows the price level of the nearest significant Harmonic Node to the current price, representing the most immediate institutional level of interest.
Cycle Matrix Section:
Cycle: Identifies the currently dominant market cycle (e.g., "MID ") based on cycle energy.
Sync: Indicates the alignment of the cyclical forces: ▲ BULLISH , ▼ BEARISH , or ◆ DIVERGENT . This is the core timing confirmation.
Signal Status Section:
A unified status bar that provides the final verdict of the engine. It will display "QUANTUM SCAN" during neutral periods, or announce the tier and direction of an active signal (e.g., "◉ TIER 1 BUY ◉" ), highlighted with the appropriate color.
🎯 SIGNAL GENERATION LOGIC
Aetherium's signal logic is built on the principle of strict, non-negotiable confluence.
Condition 1: Context (Coherence Filter): The Market Coherence must be above the Coherence Activation Level. No signals can be generated in a chaotic market.
Condition 2: Location (Liquidity Node Interaction): Price must be actively interacting with a significant Harmonic Liquidity Node.
For a Buy Signal: Price must be rejecting the Node from below (testing it as support).
For a Sell Signal: Price must be rejecting the Node from above (testing it as resistance).
Condition 3: Timing (Cycle Alignment): The Cyclical Resonance Matrix must confirm that the dominant cycles are synchronized with the intended trade direction.
Signal Tiering: The Signal Quality Mode input determines how strictly these three conditions must be met. 'Supreme' mode, for example, might require not only that the conditions are met, but that the Market Coherence is exceptionally high and the interaction with the Node is accompanied by a significant volume spike.
Signal Spacing: A final filter ensures that signals are spaced by a minimum number of bars, preventing over-alerting in a single move.
🚀 ADVANCED TRADING STRATEGIES
The Primary Confluence Strategy: The intended use of the system. Wait for a Tier 1 (Elite/Supreme) or Tier 2 (Professional/Elite) signal to appear on the chart. This represents the alignment of all three pillars. Enter after the signal bar closes, with a stop-loss placed logically on the other side of the Harmonic Node that triggered the signal.
The Coherence Context Strategy: Use the Coherence Engine as a standalone market filter. When Coherence is high (>70%), favor trend-following strategies. When Coherence is low (<50%), avoid new directional trades or favor range-bound strategies. A sharp drop in Coherence during a trend can be an early warning of a trend's exhaustion.
Node-to-Node Trading: In a high-coherence environment, use the Harmonic Liquidity Nodes as both entry points and profit targets. For example, after a BUY signal is generated at one Node, the next Node above it becomes a logical first profit target.
⚖️ RESPONSIBLE USAGE AND LIMITATIONS
Decision Support, Not a Crystal Ball: Aetherium is an advanced decision-support tool. It is designed to identify high-probability conditions based on a model of institutional behavior. It does not predict the future.
Risk Management is Paramount: No indicator can replace a sound risk management plan. Always use appropriate position sizing and stop-losses. The signals provided are probabilistic, not certainties.
Past Performance Disclaimer: The market models used in this script are based on historical data. While robust, there is no guarantee that these patterns will persist in the future. Market conditions can and do change.
Not a "Set and Forget" System: The indicator performs best when its user understands the concepts behind the three pillars. Use the dashboard and visual cues to build a comprehensive view of the market before acting on a signal.
Backtesting is Essential: Before applying this tool to live trading, it is crucial to backtest and forward-test it on your preferred instruments and timeframes to understand its unique behavior and characteristics.
🔮 CONCLUSION
The Aetherium Institutional Market Resonance Engine represents a paradigm shift from single-variable analysis to a holistic, multi-pillar framework. By quantifying the abstract concepts of market context, location, and timing into a unified, logical system, it provides traders with an unprecedented lens into the mechanics of institutional market operations.
It is not merely an indicator, but a complete analytical engine designed to foster a deeper understanding of market dynamics. By focusing on the core principles of institutional order flow, Aetherium empowers traders to filter out market noise, identify key structural levels, and time their entries in harmony with the market's underlying rhythm.
"In all chaos there is a cosmos, in all disorder a secret order." - Carl Jung
— Dskyz, Trade with insight. Trade with confluence. Trade with Aetherium.
Sentient FLDOverview of the FLD
The Future Line of Demarcation (FLD) was first proposed by JM Hurst in the 1970s as a cycle analysis tool. It is a smoothed median price plotted on a time-based chart, and displaced into the future (to the right on the chart). The amount of displacement is determined by performing a cycle analysis, the line then plotted to extend beyond the right hand edge of the chart by half a cycle wavelength.
Interactions between price and the FLD
As price action unfolds, price interacts with the FLD line, either by crossing over the line, or by finding support or resistance at the line.
Targets
When price crosses an FLD a target for the price move is generated. The target consists of a price level and also expected time.
When price reaches that target it is an indication that the cycle influencing price to move up or down has completed that action and is about to turn around.
If price fails to reach a target by the expected time, it indicates bullish or bearish pressure from longer cycles, and a change in mood of the market.
Sequence of interactions
Price interacts with the FLD in a regular sequence of 8 interactions which are labelled using the letters A - H, in alphabetical order. This sequence of interactions occurs between price and a cycle called the Signal cycle. The full sequence plays out over a single wave of a longer cycle, called the Sequence cycle. The interactions are:
A category interaction is where price crosses above the FLD as it rises out of a trough of the Sequence cycle.
B & C category interactions often occur together as a pair, where price comes back to the FLD line and finds support at the level of the FLD as the first trough of the Signal cycle forms.
D category interaction is where price crosses below the FLD as it falls towards the second trough of the Signal cycle.
E category interaction is where price crosses above the FLD again as it rises out of the second trough of the Signal cycle.
F category interaction is where price crosses below the FLD as it falls towards the next trough of the Sequence cycle.
G & H category interactions often occur together as a pair, where price comes back to the FLD line and finds resistance at the level of the FLD before a final move down into the next Sequence cycle trough.
Trading Opportunities
This sequence of interactions provides the trader with trading opportunities:
A and E category interactions involve price crossing over the FLD line, for a long trading opportunity.
D and F category interactions involve price crossing below the FLD line, for a short trading opportunity.
B and C category interactions occur where price finds support at the FLD, another long trading opportunity.
G and H category interactions occur where price finds resistance at the FLD, another short trading opportunity.
3 FLD Lines Plotted
The Sentient FLD indicator plots three FLD lines, for three primary cycles on your time-based charts:
The Signal cycle (pink color, can be changed in the settings), which is used to generate trading signals on the basis of the sequence of interactions between price and the FLD
The Mid cycle (orange color, can be changed in the settings), which is used for confirmation of the signals from the signal cycle FLD.
The Sequence cycle (green color, can be changed in the settings) which is the cycle over which the entire A - H sequence of interactions plays out.
Cycle Analysis
In addition to plotting the three FLD lines, the Sentient FLD indicator performs a cycle phasing analysis and identifies the positions of the troughs of five cycles on your chart (The Signal, Mid & Sequence cycles and two longer cycles for determining the underlying trend).
The results of this analysis are plotted by using diamond symbols to mark the timing of past troughs of the cycles, and circles to mark the timing of the next expected troughs, with lines extending to each side to represent the range of time in which the trough is expected to form. These are called circles-and-whiskers. The diamonds are stacked vertically because the troughs are synchronized in time. The circles-and-whiskers therefore are also stacked, creating a nest-of-lows which is a high probability period for a trough to form.
Identifying the Interactions
The Sentient FLD also identifies the interactions between price and each one of the three FLDs plotted on your chart, and those interactions are labelled so that you can keep track of the unfolding A - H sequence.
Next Expected Interaction
Because the Sentient FLD is able to identify the sequence of interactions, it is also able to identify the next expected interaction between price and the FLD. This enables you to anticipate levels of support or resistance, or acceleration levels where price is expected to cross through the FLD.
Cycle Table
A cycle table is displayed on the chart (position can be changed in settings). The cycle table comprises 6 columns:
The Cycle Name (CYCLE): the name of the cycle which is its nominal wavelength in words.
The Nominal Wavelength (NM): The nominal wavelength of the cycle measured in bars.
The Current Wavelength (CR): The current recent wavelength of the cycle measured in bars.
The Variation (VAR): The variation between the nominal wavelength and current wavelength as a percentage (%).
The relevant Sequence Cycle (SEQ): The cycle over which the sequence of interactions with this FLD plays out.
The Mode (MODE): Whether the cycle is currently Bearish, Neutral or Bullish.
Benefits of using the Sentient FLD
The cycle analysis shown with diamonds and circles marking the troughs, and next expected troughs of the cycles enable you to anticipate the timing of market turns (troughs and peaks in the price), because of the fact that cycles, by definition, repeat with some regularity.
The results of the cycle analysis are also displayed on your chart in a table, and enable you to understand at a glance what the current mode of each cycle is, whether bullish, bearish or neutral.
The identification of the sequence of interactions between price and the FLD enables you to anticipate the next interaction, and thereby expect either a price cross of the FLD or dynamic levels of support and resistance at the levels of the FLD lines, only visible to the FLD trader.
When the next expected interaction between price and the FLD is an acceleration point (price is expected to cross over the FLD), that level can be used as a signal for entry into a trade.
Similarly when the next expected interaction between price and the FLD is either support or resistance, that level can be used as a signal for entry into a trade when price reacts as expected, finding support or resistance.
The targets that are generated as a result of price crossing the FLD represent cycle exhaustion levels and times, and can be used as take profit exits, or as levels after which stops should be tightened.
The indicator optionally also calculates targets for longer timeframes, and displays them on your chart providing useful context for the influence of longer cycles without needing to change timeframe.
Example
In this image you can see an example of the different aspects of the indicator working on a 5 minute chart (details below):
This is what the indicator shows:
The 3 FLD lines are for the 100 minute (pink), 3 hour (orange) and 6 hour (green) cycles (refer to the cycle table for the cycle names).
Previous targets can be seen, shown as pointed labels, with the same colors.
The cycle table at the bottom left of the chart is colour coded, and indicates that the cycles are all currently running a bit long, by about 14%.
Note also the grey-colored 6 hour target generated by the 15 x minute timeframe at 12:20. When targets are close together their accuracy is enhanced.
At the foot of the chart we can see a collection of circles-and-whiskers in a nest-of-lows, indicating that a 12 hour cycle trough has been due to form in the past hour.
The past interactions between price and the signal cycle are labelled and we can see the sequence of E (with some +E post-interaction taps), F and then G-H.
The next interaction between price and the signal is the A category interaction - a long trading opportunity as price bounces out of the 12 hour cycle trough.
Notice the green upward pointing triangles on the FLD lines, indicating that they are expected to provide acceleration points, where price will cross over the FLD and move towards a target above the FLD.
The cycle table shows that the cycles of 6 hours and longer are all expected to be bullish (with the 12 hour cycle neutral to bullish).
On the basis that we are expecting a 12 hour trough to form, and the 6 hour cycle targets have been reached, and the next interaction with the signal cycle is an A category acceleration point, we can plan to enter into a long trade.
Two hours later
This screenshot shows the situation almost 2 hours later:
Notes:
The expected 12 hour cycle trough has been confirmed in the cycle analysis, and now displayed as a stack of diamonds at 12:25
Price did cross over the signal cycle FLD (the 100 minute cycle, pink FLD line) as expected. That price cross is labelled as an A category interaction at 13:00.
A 100 minute target was generated. That target was almost, but not quite reached in terms of price, indicating that the move out of the 12 hour cycle trough is not quite as bullish as would be expected (remember the 12 hour cycle is expected to be neutral-bullish). The time element of the target proved accurate however with a peak forming at the expected time. Stops could have been tightened at that time.
Notice that price then came back to the signal FLD (100 minute) line at the time that the next 100 minute cycle trough was expected (see the pink circle-and-whiskers between 13:40 and 14:25, with the circle at 14:05.
Price found support (as was expected) when it touched the signal FLD at 13:55 and 14:00, and that interaction has been labelled as a B-C category interaction pair.
We also have a 3 hour target above us at about 6,005. That could be a good target for the move.
Another 2 hours later
This screenshot shows the situation another 2 hours later:
Notes:
We can see that the 100 minute cycle trough has been confirmed at 13:45
The nest-of-lows marking the time the 3 hour cycle trough was expected is between 15:00 and 15:45, with a probable trough in price at 15:00
The sequence of interactions is labelled: A at 13:00; B-C at 14:00; another B-C (double B-C interactions are common) at 14:30; E at 15:10; +E (a post E tap) at 16:20
Price has just reached a cluster of targets at 6005 - 6006. The 3 hour target we noted before, as well as a 6 hour target and a 12 hour target from the 15 x minute timeframe.
Notice how after those targets were achieved, price has exhausted its upward move, and has turned down.
The next expected interaction with the signal cycle FLD is an F category interaction. The downward pointing red triangles on the line indicate that the interaction is expected to be a price cross down, as price moves down into the next 6 hour cycle trough.
Other Details
The Sentient FLD indicator works on all time-based charts from 10 seconds up to monthly.
The indicator works on all actively traded instruments, including forex, stocks, indices, commodities, metals and crypto.
ASE Additionals v1ASE Additionals is a statistics-driven indicator that combines multiple features to provide traders with valuable statistics to help their trading. This indicator offers a customizable table that includes statistics for VWAP with customizable standard deviation waves.
Per the empirical rule, the following is a schedule for what percent of volume should be traded between the standard deviation range:
+/- 1 standard deviation: 68.26% of volume should be trading within this range
+/- 2 standard deviation: 95.44% of volume should be trading within this range
+/- 3 standard deviation: 99.73% of volume should be trading within this range
+/- 4 standard deviation: 99.9937% of volume should be trading within this range
+/- 5 standard deviation: 99.999943% of volume should be trading within this range
+/- 6 standard deviation: 99.9999998% of volume should be trading within this range
The statistics table presents five different pieces of data
Volume Analyzed: Amount of contracts analyzed for the statistics
Volume Traded Inside Upper Extreme: Calculated by taking the amount of volume traded inside the Upper Extreme band divided by the total amount of contracts analyzed
Volume Traded Inside Lower Extreme: Calculated by taking the amount of volume traded inside the Lower Extreme band divided by the total amount of contracts analyzed
Given the user’s inputs, they will see the upper and lower extremes of the day. For example, if the user changed the inner st. dev input to 2, 95.44% of the volume should be traded within the inner band. If the user changed the outer st. dev input to 3, 99.73% of the volume should be traded within the outer band. Thus, statistically, 2.145% ((99.73%-95.44%)/2) of volume should be traded between the upper and lower band fill.
In the chart above, the bands are the 2nd and 3rd standard deviation inputs. We notice that out of the 151 Million Contracts , the actual percentage of volume traded in the upper extreme was 2.7% , and the actual percentage of the volume traded in the lower extreme was 3.3% . Given the empirical rule, about 2.145% of the volume should be traded in the upper extreme band, and 2.145% of the volume should be traded in the lower extreme band. Based on the statistics table, the empirical rule is true when applied to the volume-weighted average price.
The trader should recognize that statistics is all about probability and there is a margin for error, so the bands should be used as a bias, not an entry. For example, given the +/-2 and 3 standard deviations, statistically, if 2.145% of the volume is traded within the upper band extreme, you shouldn’t look for a long trade if the current price is in the band. Likewise, if 2.145% of the volume is traded within the lower band extreme, you shouldn’t look for a short trade if the current price is in the band.
Additionally, we provide traders with the Daily, Weekly, and Monthly OHLC levels. Open, High, Low, and Close are significant levels, especially on major timeframes. Once price has touched the level, the line changes from dashed/dotted to solid.
Features
VWAP Price line and standard deviation waves to analyze the equilibrium and extremes of the sessions trend
Previous Day/WEEK/Month OHLC levels provide Major timeframe key levels
Settings
VWAP Equilibrium: Turn on the VWAP line
VWAP Waves: Turn on the VWAP standard deviation waves
Inner St. Dev: Changes the inner band standard deviation to show the percentage of volume traded within
Outer St. Dev: Changes the outer band standard deviation to show the percentage of volume traded within
Upper Extreme: Change the color of the upper VWAP wave
Lower Extreme: Change the color of the lower VWAP wave
Wave Opacity: Change the opacity of the waves (0= completely transparent, 100=completely solid)
Statistics Table: Turn on or off the statistics table
Statistics Table Settings: Change the Table Color, Text Color, Text Size, and Table Position
Previous Day/Week/Month OHLC: Choose; All, Open, Close, High, Low, and the color of the levels
OHLC Level Settings: Change the OHLC label color, line style, and line width
How to Use
The VWAP price line acts as the 'Fair Value' or the 'Equilibrium' of the price session. Just as the VWAP Waves show the session's upper and lower extreme possibilities. While we can find entries from VWAP , our analysis uses it more as confirmation. OHLC levels are to be used as support and resistance levels. These levels provide us with great entry and target opportunities as they are essential and can show pivots in price action.
EWO Breaking Bands & XTLElliott Wave Principle, developed by Ralph Nelson Elliott , proposes that the seemingly chaotic behaviour of the different financial markets isn’t actually chaotic. In fact the markets moves in predictable, repetitive cycles or waves and can be measured and forecast using Fibonacci numbers. These waves are a result of influence on investors from outside sources primarily the current psychology of the masses at that given time. Elliott wave predicts that the prices of the a traded currency pair will evolve in waves: five impulsive waves and three corrective waves. Impulsive waves give the main direction of the market expansion and the corrective waves are in the opposite direction (corrective wave occurrences and combination corrective wave occurrences are much higher comparing to impulsive waves)
The Elliott Wave Oscillator ( EWO ) helps identifying where you are in the 5 / 3 Elliott Waves , mainly the highest/lowest values of the oscillator might indicate a potential bullish / bearish Wave 3. Mathematically expressed, EWO is the difference between a 5 period and 35 period moving average. In this study instead 35-period, Fibonacci number 34 is implemented for the slow moving average and formula becomes ewo = sma (HL2, 5) - sma (HL2, 34)
The Elliott Wave Oscillator enables traders to track Elliott Wave counts and divergences. It allows traders to observe when an existing wave ends and when a new one begins. Included with the EWO are the breakout bands that help identify strong impulses.
The Expert Trend Locator ( XTL ) was developed by Tom Joseph (in his book Applying Technical Analysis) to identify major trends, similar to Elliott Wave 3 type swings.
Blue bars are bullish and indicate a potential upwards impulse.
Red bars are bearish and indicate a potential downwards impulse.
White bars indicate no trend is detected at the moment.
Added "TSI Arrows". The arrows is intended to help the viewer identify potential turning points. The presence of arrows indicates that the TSI indicator is either "curling" up under the signal line, or "curling" down over the signal line. This can help to anticipate reversals, or moves in favor of trend direction.
Harmonic Patterns ProHello All,
We need to make things better & better to solve the puzzle and I try to do my best on this way for the community. now I am here with my Harmonic Patterns Pro script.
Harmonic Pattern recognition is the basic and primary ability any trader develops in technical analysis. Harmonic pattern recognition takes extensive practice and repetitive exposure. in general chart patterns are categorized into “continuous” and “reversal” patterns. Harmonic patterns construct geometric pattern structures using Fibonacci sequences. These harmonic structures identified as specified harmonic patterns provide unique opportunities for traders, such as potential price movements and key turning or trend reversal points. This script is developed to find following patterns by using the options you set. I have to say that this is not a strategy and you should not use this script blindly, instead, I strongly recommend you to create your own strategy using this script with other tools/indicators, such moving averages, Support/Resistance levels, volume indicators, sentiment indicators etc.
- Following Harmonic Patterns are available in this version:
-->Gartley
-->Butterfly
-->Bat
-->Crab
-->Shark
-->Cypher
-->Alternate Bat
-->Deep Crab
-->5-0
-->3-Drive
-->AB=CD
-->Descending Triangle
-->Ascending Triangle
-->Symmetrical Triangle
-->Double Top
-->Double Bottom
How the script works and finds harmonic patterns:
- It uses zigzag like other harmonic pattern script but there is a difference. this scripts searches up to 200 bars, finds/creates up to 200 XABCD using zigzag waves and searches predefined harmonic patterns
- It can find multiple harmonic patterns on a candles with different sizes and lengths
- Each pattern is shown using its own color (you can set 8 different colors)
- it shows Entry, Target1, Target2 and Stop-loss levels for each found Patterns
- It shows pattern validation zones for each found pattern
- it has all-in-one alerts. you set the alerts you want in the indicator options and you create only 1 alert for each symbol.
- it has prediction future and it can show many predicted patterns at the same time, each predicted patterns validations zones are shown separately
- While on real-time bar it searches and shows patterns for the visible area
it has followng alerts: . these in all-in-one alerts. it means that you choose the alerts in the options and enables any of them and then create only one for each symbol. and you get eany alert you choose. (" Any alert() function call "). in this version "Any alert() function call" alert is only alert you can use, if I get some requests I can try to other alerts as well.
New Pattern Found
Pattern Updated
Entered Position
Reached Target
Stop-loss
Validation zone is calculated using XABC points any pattern by using Y-Axis error rate. so if you increase Y-Axis error rate then the script can find much more Harmonic patterns.
X-Axis Error Rate is used for a few pattern such AB=CD for the distance of AB wave and CD wave.
The script can show Recommended Entry, Target 1, Target 2 and stop-loss levels for each active patterns. of course you can use these levels or you can set your own levels. you can see the screenshot below.
The script can show statistics panel. when statistic panel is enabled then no pattern is shown on the chart, the script shows ONLY statistics panel. This was done because of complexity of the script.
If you enables Prediction then pattern checks all possible XABC formations in the last 200 bars and finds/shows predicted patterns if there is any.
if you "replaying" then the script searches patterns only for last bar (if any update on zigzag on last bar), not for historical ones. you should take care while you use "Replay" feature of Tradingview
Now lets see the options:
Minimum ZigZag Period: this is minimum Zigzag Period to create new Zigzag wave. default value is 10 and minimum value is 4
Y-Axis Error Rate %: this is the error rate to create validation zones for each pattern, there is almost no perfect pattern, so we try to create a zone using error rate
X-Axis Error Rate % : this is used for a few pattern (such AB=CD) to check wave lengths on time basis
Minimum Pattern Length: This is Minimum Length for the Patterns to be searched. in Number of Bars
Maximum Pattern Length : This is Maximum Lengths for the Patterns to be searched. in Number of Bars
Max Number of XABCD to search: Maximum Number of ABCD to search pattern on each move, there are many possible XABCDs on the chart, this limitation is the number for how many of them will be searched
Find Patterns for: is the option about taking position. there are three options: "Long and Short", "Only Long", "Only Short"
Max Patterns on Each Bar: Maximum Number of Patterns that can be found on each bar, by default it's 3
Keep Pattern Until: you have two option "Target1" and "Target2". when a pattern found and if it reach any of these targets it is accepted as it's reached target and removed. this is also used inthe statictics panel!
Show Recommended Entries & Targets: if enabled then the script can show "Recommended" Entry, target1, target2 and stop-loss leves. you can use these levels or you can use your own calculation for each pattern
Entry = % of Target 2 : Entry Level for each pattern is calculated using the distance between D positon of the pattern and target 2. by default it's 16%, you can set it as you wish
Entry&Target Line Style: you can set line style for entry/target/stop-loss levels
Show Pattern Validation Zones: as explained above, for each pattern validation zone is created using error rate (Y-axis error rate). you can see it for each pattern
Source for Invalidation: this source is used for validation zones. there is two options: Close or High/Low. this source is used while invalidated the pattern. by default it used "close" price as source
Line Style: this is line style for validation zones, solid, dashed or dotted
Pattern Prediction/Possible Patterns: if you enable this option then the script calculates/searches possbile patterns and shows their levels in a label if there is one or more
Show Label & Zone: this is about how you want to see predictions, there are two choices: "Show Only Label", "Show Label & Zone"
Show Statistics Panel : if you enable this option then the script starts searching all harmonic patterns from the first bar for the last bar and keeps statistics for all of them and the shows in a table. you can see screenshot below
Panel Position: you can set panel location of statistics panel using this option
Show Rates Between Waves: if you enable this option then rate between the waves are shown. by default it's enabled
Keep Last Pattern on the Chart : if you enable this option then even if pattern is invalidated/reach target/stop-loss it stays on the chart until new pattern is found. by default it's enabled
Line Style : line style for the last pattern on the chart
Patterns to Search: you have options to enable/disable the patterns listed above to find&show, you can enable/disable any pattern in the list. by default all patterns are enabled except AB=CD pattern
in the ALERTS menu you have many options to enable/disable the alerts you want. Alerts contain Symbol name, Pattern name, Direction as Long/Short, Recommended Entry, Targets, SL levels.
- New Pattern Found
- Pattern Updated
- Entered Position
- Reached Target
- Stop-loss
Show Zig Zag: if you want to see Zig Zag then you should enable this option, and you can set the colors for the Zig zag. by default it's disabled.
and some other options for coloring and line styles of the patterns..
This is how XABCD points found using zigzag waves, I tried to explain it in the video below:
Validation zones and Entry, Target1, Target2 and Stop-loss levels:
Each pattern has its own color, you can see which levels, letters, lines etc belongs to which pattern:
Pattern prediction: you can enable it and change its background color:
How Statistics panel looks like. if there is active pattern then it's shown in different color in the table
This screenshot shows how the script finds and shows multiple patterns on a candle:
And some examples for triangles and Double top/bottom patterns:
Symmetrical triangle:
Ascending triangle:
Double bottom
and many others..
While using different time frames the script can find same patterns, in the following screenshots you can see how same patterns found on 5 and 10 min chart. of course this depends on the Zigzag Period
in this video, the idea and the indicator options is explained:
I can say that this is very complex script and it takes very long time to develop. I used my all programming ability and Pine ability to develop it. I hope you like it and make a lot of profit.
DISCLAIMER: No sharing, copying, reselling, modifying, or any other forms of use are authorized for the documents, script / strategy, and the information published with them. This informational planning script / strategy is strictly for individual use and educational purposes only. This is not financial or investment advice. Investments are always made at your own risk and are based on your personal judgement. I am not responsible for any losses you may incur. Please invest wisely.
Enjoy!
Script payant
Ichimoku Kinkō HyōThe Ichimoku Kinko Hyo is an trading system developed by the late Goichi Hosoda (pen name "Ichimokusanjin") when he was the general manager of the business conditions department of Miyako Shinbun, the predecessor of the Tokyo Shimbun. Currently, it is a registered trademark of Economic Fluctuation Research Institute Co., Ltd., which is run by the bereaved family of Hosoda as a private research institute.
The Ichimoku Kinko Hyo is composed of time theory, price range theory (target price theory) and wave movement theory. Ichimoku means "At One Glace". The equilibrium table is famous for its span, but the first in the equilibrium table is the time relationship.
In the theory of time, the change date is the day after the number of periods classified into the basic numerical value such as 9, 17, 26, etc., the equal numerical value that takes the number of periods of the past wave motion, and the habit numerical value that appears for each issue is there. The market is based on the idea that the buying and selling equilibrium will move in the wrong direction. Another feature is that time is emphasized in order to estimate when changes will occur.
In the price range theory, there are E・V・N・NT calculated values and multiple values of 4 to 8E as target values. In addition, in order to determine the momentum and direction of the market, we will consider other price ranges and ying and yang numbers.
If the calculated value is realized on the change date calculated by each numerical value, the market price is likely to reverse.
転換線 (Tenkansen) (Conversion Line) = (highest price in the past 9 periods + lowest price) ÷ 2
基準線 (Kijunsen) (Base Line) = (highest price in the past 26 periods + lowest price) ÷ 2
It represents Support/Resistance for 16 bars. It is a 50% Fibonacci Retracement. The Kijun sen is knows as the "container" of the trend. It is prefect to use as an initial stop and/or trailing stop.
先行スパン1 (Senkou span 1) (Lagging Span 1) = {(conversion value + reference value) ÷ 2} 25 periods ahead (26 periods ahead including the current day, that is)
先行スパン2 (Senkou span 2) (Lagging Span 2) = {(highest price in the past 52 periods + lowest price) ÷ 2} 25 periods ahead (26 periods ahead including the current day, that is)
遅行スパン (Chikou span) (Lagging Span) = (current candle closing price) plotted 26 periods before (that is, including the current day) 25 periods ago
It is the only Ichimoku indicator that uses the closing price. It is used for momentum of the trend.
The area surrounded by the two lagging span lines is called a cloud. This is the foundation of the system. It determines the sentiment (Bull/Bear) for the insrument. If price is above the cloud, the instrument is bullish. If price is below the cloud, the instrument is bearish.
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The wave theory of the Ichimoku Kinko Hyo has the following waves.
All about the rising market. If it is the falling market, the opposite is true.
I wave rise one market price.
V wave the market price that raises and lowers.
N wave the market price for raising, lowering, and raising.
P wave the high price depreciates and the low price rises with the passage of time. Leave either.
Y wave the high price rises and the low price falls with the passage of time. Leave either.
S wave A market in which the lowered market rebounds and rises at the previous high level.
There are the above 6 types but the basis of the Ichimoku Kinko Hyo is the N wave of 3 waves.
In Elliott wave theory and similar theories, basically there are 5 waves but 5 waves are a series of 2 and 3 waves N, 3 for 7 waves, 4 for 9 waves and so on.
Even if it keep continuing, it will be based on N wave. In addition, since the P wave and the Y wave are separated from each other, they can be seen as N waves from a large perspective.
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There are basic E・V・N・NT calculated values and several other calculation methods for the Ichimoku Kinko Hyo. It is the only calculated value that gives a concrete value in the Ichimoku Kinko Hyo, which is difficult to understand, but since we focus only on the price difference and do not consider the supply and demand, it is forbidden to stick to the calculated value alone.
(The calculation method of the following five calculated values is based on the rising market price, which is raised from the low price A to the high price B and lowered from the high price B to the low price C. Therefore, the low price C is higher than the low price A)
E calculated value The amount of increase from the low price A to the high price B is added to the high price B. = B + (BA)
V calculated value Adds the amount of decline from the high price B to the low price C to the high price B. = B + (BC)
N calculated value The amount of increase from the low price A to the high price B is added to the low price C. = C + (BA)
NT calculated value Adds the amount of increase from the low price A to the low price C to the low price C. = C + (CA)
4E calculated value (four-layer double / quadruple value) Adds three times the amount of increase from the low price A to the high price B to the high price B. = B + 3 × (BA)
Calculated value of P wave The upper price is devalued and the lower price is rounded up, and the price range of both is the same.
Calculated value of Y wave The upper price is rounded up and the lower price is rounded down, and the price range of both is the same.
[blackcat] L2 Ehlers Even Better SinwaveLevel: 2
Background
John F. Ehlers introduced Even Better sinwave Indicator in his "Cycle Analytics for Traders" chapter 12 on 2013.
Function
The original Sinewave Indicator was created by seeking the dominant cycle phase angle that had the best correlation between the price data and a theoretical dominant cycle sine wave. The Even Better Sinewave Indicator skips all the cycle measurements completely and relies on a strong normalization of the waveform at the output of a modified roofing filter. The modified roofing filter uses a single-pole high-pass filter to deliberately retain the longer-period trend components. The single-pole high-pass filter basically levels the amplitude of all the cycle components that would otherwise be larger with longer wavelengths due to Spectral Dilation. Therefore, when the waveform is normalized to the power in the waveform over a short period of time, the longer wavelength contributions tend to be an indication to stay in a trade when the market is in a trend.
The Even Better Sinewave Indicator works extraordinarily well when the market is in a trend mode. This means that the spectacular failures of most swing wave indicators are mitigated when the expected price turning point does not occur.
Although Dr. Ehlers admitted he had not studied it extensively, it appears that the Even Better Sinewave Indicator works well on futures intraday data. It takes a position in the correct direction and tends to stay with the good trades without excessive whipsawing.
Key Signal
Wave --> Even Better sinwave Indicator fast line
Trigger --> Even Better sinwave Indicator slow line
Pros and Cons
100% John F. Ehlers definition translation of original work, even variable names are the same. This help readers who would like to use pine to read his book. If you had read his works, then you will be quite familiar with my code style.
Remarks
The 55th script for Blackcat1402 John F. Ehlers Week publication.
Readme
In real life, I am a prolific inventor. I have successfully applied for more than 60 international and regional patents in the past 12 years. But in the past two years or so, I have tried to transfer my creativity to the development of trading strategies. Tradingview is the ideal platform for me. I am selecting and contributing some of the hundreds of scripts to publish in Tradingview community. Welcome everyone to interact with me to discuss these interesting pine scripts.
The scripts posted are categorized into 5 levels according to my efforts or manhours put into these works.
Level 1 : interesting script snippets or distinctive improvement from classic indicators or strategy. Level 1 scripts can usually appear in more complex indicators as a function module or element.
Level 2 : composite indicator/strategy. By selecting or combining several independent or dependent functions or sub indicators in proper way, the composite script exhibits a resonance phenomenon which can filter out noise or fake trading signal to enhance trading confidence level.
Level 3 : comprehensive indicator/strategy. They are simple trading systems based on my strategies. They are commonly containing several or all of entry signal, close signal, stop loss, take profit, re-entry, risk management, and position sizing techniques. Even some interesting fundamental and mass psychological aspects are incorporated.
Level 4 : script snippets or functions that do not disclose source code. Interesting element that can reveal market laws and work as raw material for indicators and strategies. If you find Level 1~2 scripts are helpful, Level 4 is a private version that took me far more efforts to develop.
Level 5 : indicator/strategy that do not disclose source code. private version of Level 3 script with my accumulated script processing skills or a large number of custom functions. I had a private function library built in past two years. Level 5 scripts use many of them to achieve private trading strategy.
Right Sided Ricker Moving Average And The Gaussian DerivativesIn general gaussian related indicators are built by using the gaussian function in one way or another, for example a gaussian filter is built by using a truncated gaussian function as filter kernel (kernel refer to the set weights) and has many great properties, note that i say truncated because the gaussian function is not supposed to be finite. In general the gaussian function is represented by a symmetrical bell shaped curve, however the gaussian function is parametric, and the user might adjust the position of the peak as well as the width of the curve, an indicator using this parametric approach is the Arnaud Legoux moving average (ALMA) who posses a length parameter controlling the filter length, a peak parameter controlling the position of the peak of the gaussian function as well as a width parameter, those parameters can increase/decrease the lag and smoothness of the moving average output.
However what about the derivatives of the gaussian function ? We don't talk much about them and thats a pity because they are extremely interesting and have many great properties as well, therefore in this post i'll present a low lag moving average based on the modification of the 2nd order derivative of the gaussian function, i believe this post will be extremely informative and i hope you will enjoy reading it, if you are not a math person you can skip the introduction on gaussian derivatives and their properties used as filter kernel.
Gaussian Derivatives And The Ricker Wavelet
The notion of derivative is continuous, so we will stick with the term discrete derivative instead, which just refer to the rate of change in the function, we have a change function in pinescript, and we will be using it to show an approximation of the gaussian function derivatives.
Earlier i used the term 2nd order derivative, here the derivative order refer to the order of differentiation, that is the number of time we apply the change function. For example the 0 (zeroth) order derivative mean no differentiation, the 1st order derivative mean we use differentiation 1 time, that is change(f) , 2nd order mean we use differentiation 2 times, that is change(change(f)) , derivates based on multiple differentiation are called "higher derivative". It will be easier to show a graphic :
Here we can see a normal gaussian function in blue, its scaled 1st order derivative in orange, and its scaled 2nd derivative in green, note that i use scaled because i used multiplication in order for you to see each curve, else it would have been less easy to observe them. The number of time a gaussian function derivative cross 0 is based on the order of differentiation, that is 2nd order = the function crossing 0 two times.
Now we can explain what is the Ricker wavelet, the Ricker wavelet is just the normalized 2nd order derivative of a gaussian function with inverted sign, and unlike the gaussian function the only thing you can change is the width parameter. The formula of the Ricker wavelet is show'n here en.wikipedia.org , where sigma is the width parameter.
The Ricker wavelet has this look :
Because she is shaped like a sombrero the Ricker wavelet is also called "mexican hat wavelet", now what would happen if we used a Ricker wavelet as filter kernel ? The response is that we would end-up with a bandpass filter, in fact the derivatives of the gaussian function would all give the kernel of a bandpass filter, with higher order derivatives making the frequency response of the filter approximate a symmetrical gaussian function, if i recall a filter using the first order derivative of a gaussian function would give a frequency response that is left skewed, this skewness is removed when using higher order derivatives.
The Indicator
I didn't wanted to make a bandpass filter, as lately i'am more interested in low-lag filters, so how can we use the Ricker wavelet to make a low-lag low-pass filter ? The response is by taking the right side of the Ricker wavelet, and since values of the wavelets are negatives near the border we know that the filter passband is non-monotonic, that is we know that the filter will have low-lag as frequencies in the passband will be amplified.
So taking the right side of the Ricker wavelet only mean that t has to be greater than 0 and linearly increasing, thats easy, however the width parameter can be tricky to use, this was already the case with ALMA, so how can we work with it ? First it can be seen that values of width needs to be adjusted based on the filter length.
In red width = 14, in green width = 5. We can see that an higher values of width would give really low weights, when the number of negative weights is too important the filter can have a negative group delay thus becoming predictive, this simply mean that the overshoots/undershoots will be crazy wild and that a great fit will be impossible.
Here two moving averages using the previous described kernels, they don't fit the price well at all ! In order to fix this we can simply define width as a function of the filter length, therefore the parameter "Percentage Width" was introduced, and simply set the width of the Ricker wavelet as p percent of the filter length. Lower values of percent width reduce the lag of the moving average, but lets see precisely how this parameter influence the filter output :
Here the filter length is equal to 100, and the percent width is equal to 60, the fit is quite great, lower values of percent width will increase overshoots, in fact the filter become predictive once the percent width is equal or lower to 50.
Here the percent width is equal to 50. Higher values of percent width reduce the overshoots, and a value of 100 return a filter with no overshoots that is suited to act as a lagging moving average.
Above percent width is set to 100. In order to make use of the predictive side of the filter, it would be great to introduce a forecast option, however this require to find the best forecast horizon period based on length and width, this is no easy task.
Finally lets estimate a least squares moving average with the proposed moving average, you know me...a percent width set to 63 will return a relatively good estimate of the LSMA.
LSMA in green and the proposed moving in red with percent width = 63 and both length = 100.
Conclusion
A new low-lag moving average using a right sided Ricker wavelet as filter kernel has been introduced, we have also seen some properties of gaussian derivatives. You can see that lately i published more moving averages where the user can adjust certain properties of the filter kernel such as curve width for example, if you like those moving averages you can check the Parametric Corrective Linear Moving Averages indicator published last month :
I don't exclude working with pure forms of gaussian derivatives in the future, as i didn't published much oscillators lately.
Thx for reading !
Ord Volume [LucF]Tim Ord came up with the Ord Volume concept. The idea is similar to Weis Wave , except that where Weis Wave keeps a cumulative tab of each wave’s successive volume columns, Ord Volume tracks the wave's average volume .
Features
You can choose to distinguish the area’s colors when the average is rising/falling (default).
You can show an EMA of the wave averages, which is different than an EMA on raw volume.
You can show (default) the last wave’s ending average over the current wave, to help in comparing relative levels.
You can change the length of the trend that needs to be broken for a new wave to start, as well as the price used in trend detection.
Use Cases
As with Weis Wave, what I look at first are three characteristics of the waves: their length, height and slope. I then compare those to the corresponding price movements, looking for discrepancies. For example, consecutive bearish waves of equal strength associated with lesser and lesser price movements are often a good indication of an impeding reversal.
Because Ord Volume uses average rather than cumulative volume, I find it is often easier to distinguish what is going on during waves, especially exhaustion at the end of waves.
Tim Ord has a method for entries and exits where he uses Ord Volume in conjunction with tests of support and resistance levels. Here are two articles published in 2004 where Ord explains his technique:
pr.b5z.net
n.b5z.net
Note
Being dependent on volume information as it is currently available in Pine, which does not include a practical way to retrieve delta volume information, the indicator suffers the same lack of precision as most other Pine-built volume indicators. For those not aware of the issue, the problem is that there is no way to distinguish the buying and selling volume (delta volume) in a bar, other than by looping through inside intervals using the security() function, which for me makes performance unsustainable in day to day use, while only providing an approximation of delta volume.
Gann Levels (Auto) by RRR📌 Gann Levels (Auto) — Intraday, Swing & Elliott Wave Precision Tool
Gann Levels (Auto) is a high-accuracy price-reaction indicator designed for intraday scalpers, swing traders, and Elliott Wave traders who want clean, auto-updating support and resistance levels without manually drawing anything.
The indicator automatically detects the latest swing high & swing low and plots the 8 Gann Octave Levels between them. These levels act as a complete price map—showing equilibrium, structure, trend continuation zones, and reversal points with extreme precision.
🔥 Why This Indicator Stands Out
✔ Fully automatic swing detection
Levels update as structure evolves — no manual adjustments.
✔ All Gann Octave levels
Plots 1/8 through 8/8 including the critical 4/8 midpoint.
✔ Intraday-optimized
Exceptional on 1m, 3m, 5m, and 15m charts.
✔ Ultra-clean support & resistance
Levels act as reliable barriers and breakout zones.
⭐ MOST IMPORTANT LEVELS FOR INTRADAY
4/8 – Midpoint (Major Decision Pivot)
Strongest Gann level.
Controls trend or reversal for the session.
Breakout → Trend Day
Rejection → Reversal Day
8/8 & 0/8 – Extreme Structure Edges
Most likely zones for intraday reversals.
Perfect for scalp entries when combined with volume exhaustion.
🎯 How to Trade ELLIOTT WAVE Using Gann Levels
This indicator is exceptionally powerful when combined with Elliott Wave Theory.
Here is how to use it wave-by-wave:
🔵 Wave 2 → Identify Bottom Using 0/8 or 1/8 Levels
Wave 2 typically retraces deep but remains above key structure.
Gann confirmation:
Price stops at 0/8 or 1/8 zone
Rejection wick + low volume breakdown attempt
Bullish intent starts forming
This gives a perfect Wave 3 entry zone.
🔴 Wave 3 → Breakout Above 4/8 Midpoint
Wave 3 is the strongest impulsive wave.
The 4/8 level works like a force-field.
Wave 3 confirmation:
Price breaks and retests 4/8
Strong volume
No deep pullbacks after break
This is one of the most reliable Elliott + Gann trades.
🟡 Wave 4 → Uses 3/8 or 5/8 as Support/Resistance
Wave 4 is corrective and shallow compared to Wave 2.
Gann alignment:
Wave 4 often consolidates between 3/8 and 5/8
Levels act like range boundaries
Avoid trading inside chop; wait for breakout
This gives perfect continuation entries for Wave 5.
🟣 Wave 5 → Ends Near 7/8 or 8/8 Extreme Zone
Wave 5 usually ends in overbought territory.
Gann confirmation:
Price hits 7/8 or 8/8
Momentum weakens
Divergence builds (RSI/MACD optional)
Last push = exhaustion
This is where reversals or major pullbacks begin.
💥 BONUS: Corrective Waves (A-B-C)
Wave A:
Often rejects from 4/8 or 5/8.
Wave B:
Typically trapped between 3/8–5/8.
Wave C:
Usually ends around 0/8 (for bullish trend)
or 8/8 (for bearish trend).
These zones give ultra-high confidence entries.
⚙️ Who This Indicator Is Perfect For
Elliott Wave traders
Intraday scalpers
Swing traders
Price action & structure traders
Traders who want automatic support-resistance levels
Traders who want clean, non-cluttered levels
⚠️ Disclaimer
This indicator is for educational purposes only.
Trading involves risk. Always use proper risk management.
Aethix Cipher DivergencesAethix Cipher Divergences v6
Core Hook: Custom indicator inspired by VuManChu B, Grok-enhanced for crypto intel—blends WaveTrend (WT) oscillator with multi-divergences for buy/sell circles (green/teal buys #00FFFF, red sells) and dots (divs, gold overbought alerts).
Key Features:
WaveTrend Waves: Dual waves (teal WT1, darker teal WT2) with VWAP (purple for neon vibe), overbought/oversold lines, crosses for signals.
Divergences: Regular/hidden for WT, RSI, Stoch—red bearish, green bullish dots; extra range for deeper insights.
RSI + MFI Area: Colored area (green positive, red negative) for sentiment/volume flow.
Stochastic RSI: K/D lines with fill for overbought/oversold trends.
Schaff Trend Cycle: Purple line for cycle smoothing.
Sommi Patterns: Flags (pink bearish, blue bullish) and diamonds for HTF patterns, purple higher VWAP.
MACD Colors on WT: Dynamic WT shading based on MACD for enhanced reads.
Information-Geometric Market DynamicsInformation-Geometric Market Dynamics
The Information Field: A Geometric Approach to Market Dynamics
By: DskyzInvestments
Foreword: Beyond the Shadows on the Wall
If you have traded for any length of time, you know " the feeling ." It is the frustration of a perfect setup that fails, the whipsaw that stops you out just before the real move, the nagging sense that the chart is telling you only half the story. For decades, technical analysis has relied on interpreting the shadows—the patterns left behind by price. We draw lines on these shadows, apply indicators to them, and hope they reveal the future.
But what if we could stop looking at the shadows and, instead, analyze the object casting them?
This script introduces a new paradigm for market analysis: Information-Geometric Market Dynamics (IGMD) . The core premise of IGMD is that the price chart is merely a one-dimensional projection of a much richer, higher-dimensional reality—an " information field " generated by the collective actions and beliefs of all market participants.
This is not just another collection of indicators. It is a unified framework for measuring the geometry of the market's information field—its memory, its complexity, its uncertainty, its causal flows—and making high-probability decisions based on that deeper reality. By fusing advanced mathematical and informational concepts, IGMD provides a multi-faceted lens through which to view market behavior, moving beyond simple price action into the very structure of market information itself.
Prepare to move beyond the flatland of the price chart. Welcome to the information field.
The IGMD Framework: A Multi-Kernel Approach
What is a Kernel? The Heart of Transformation
In mathematics and data science, a kernel is a powerful and elegant concept. At its core, a kernel is a function that takes complex, often inscrutable data and transforms it into a more useful format. Think of it as a specialized lens or a mathematical "probe." You cannot directly measure abstract concepts like "market memory" or "trend quality" by looking at a price number. First, you must process the raw price data through a specific mathematical machine—a kernel—that is designed to output a measurement of that specific property. Kernels operate by performing a sort of "similarity test," projecting data into a higher-dimensional space where hidden patterns and relationships become visible and measurable.
Why do creators use them? We use kernels to extract features —meaningful pieces of information—that are not explicitly present in the raw data. They are the essential tools for moving beyond surface-level analysis into the very DNA of market behavior. A simple moving average can tell you the average price; a suite of well-chosen kernels can tell you about the character of the price action itself.
The Alchemist's Challenge: The Art of Fusion
Using a single kernel is a challenge. Using five distinct, computationally demanding mathematical engines in unison is an immense undertaking. The true difficulty—and artistry—lies not just in using one kernel, but in fusing the outputs of many . Each kernel provides a different perspective, and they can often give conflicting signals. One kernel might detect a strong trend, while another signals rising chaos and uncertainty. The IGMD script's greatest strength is its ability to act as this alchemist, synthesizing these disparate viewpoints through a weighted fusion process to produce a single, coherent picture of the market's state. It required countless hours of testing and calibration to balance the influence of these five distinct analytical engines so they work in harmony rather than cacophony.
The Five Kernels of Market Dynamics
The IGMD script is built upon a foundation of five distinct kernels, each chosen to probe a unique and critical dimension of the market's information field.
1. The Wavelet Kernel (The "Microscope")
What it is: The Wavelet Kernel is a signal processing function designed to decompose a signal into different frequency scales. Unlike a Fourier Transform that analyzes the entire signal at once, the wavelet slides across the data, providing information about both what frequencies are present and when they occurred.
The Kernels I Use:
Haar Kernel: The simplest wavelet, a square-wave shape defined by the coefficients . It excels at detecting sharp, sudden changes.
Daubechies 2 (db2) Kernel: A more complex and smoother wavelet shape that provides a better balance for analyzing the nuanced ebb and flow of typical market trends.
How it Works in the Script: This kernel is applied iteratively. It first separates the finest "noise" (detail d1) from the first level of trend (approximation a1). It then takes the trend a1 and repeats the process, extracting the next level of cycle (d2) and trend (a2), and so on. This hierarchical decomposition allows us to separate short-term noise from the long-term market "thesis."
2. The Hurst Exponent Kernel (The "Memory Gauge")
What it is: The Hurst Exponent is derived from a statistical analysis kernel that measures the "long-term memory" or persistence of a time series. It is the definitive measure of whether a series is trending (H > 0.5), mean-reverting (H < 0.5), or random (H = 0.5).
How it Works in the Script: The script employs a method based on Rescaled Range (R/S) analysis. It calculates the average range of price movements over increasingly larger time lags (m1, m2, m4, m8...). The slope of the line plotting log(range) vs. log(lag) is the Hurst Exponent. Applying this complex statistical analysis not to the raw price, but to the clean, wavelet-decomposed trend lines, is a key innovation of IGMD.
3. The Fractal Dimension Kernel (The "Complexity Compass")
What it is: This kernel measures the geometric complexity or "jaggedness" of a price path, based on the principles of fractal geometry. A straight line has a dimension of 1; a chaotic, space-filling line approaches a dimension of 2.
How it Works in the Script: We use a version based on Ehlers' Fractal Dimension Index (FDI). It calculates the rate of price change over a full lookback period (N3) and compares it to the sum of the rates of change over the two halves of that period (N1 + N2). The formula d = (log(N1 + N2) - log(N3)) / log(2) quantifies how much "longer" and more convoluted the price path was than a simple straight line. This kernel is our primary filter for tradeable (low complexity) vs. untradeable (high complexity) conditions.
4. The Shannon Entropy Kernel (The "Uncertainty Meter")
What it is: This kernel comes from Information Theory and provides the purest mathematical measure of information, surprise, or uncertainty within a system. It is not a measure of volatility; a market moving predictably up by 10 points every bar has high volatility but zero entropy .
How it Works in the Script: The script normalizes price returns by the ATR, categorizes them into a discrete number of "bins" over a lookback window, and forms a probability distribution. The Shannon Entropy H = -Σ(p_i * log(p_i)) is calculated from this distribution. A low H means returns are predictable. A high H means returns are chaotic. This kernel is our ultimate gauge of market conviction.
5. The Transfer Entropy Kernel (The "Causality Probe")
What it is: This is by far the most advanced and computationally intensive kernel in the script. Transfer Entropy is a non-parametric measure of directed information flow between two time series. It moves beyond correlation to ask: "Does knowing the past of Volume genuinely reduce our uncertainty about the future of Price?"
How it Works in the Script: To make this work, the script discretizes both price returns and the chosen "driver" (e.g., OBV) into three states: "up," "down," or "neutral." It then builds complex conditional probability tables to measure the flow of information in both directions. The Net Transfer Entropy (TE Driver→Price minus TE Price→Driver) gives us a direct measure of causality . A positive score means the driver is leading price, confirming the validity of the move. This is a profound leap beyond traditional indicator analysis.
Chapter 3: Fusion & Interpretation - The Field Score & Dashboard
Each kernel is a specialist providing a piece of the puzzle. The Field Score is where they are fused into a single, comprehensive reading. It's a weighted sum of the normalized scores from all five kernels, producing a single number from -1 (maximum bearish information field) to +1 (maximum bullish information field). This is the ultimate "at-a-glance" metric for the market's net state, and it is interpreted through the dashboard.
The Dashboard: Your Mission Control
Field Score & Regime: The master metric and its plain-English interpretation ("Uptrend Field", "Downtrend Field", "Transitional").
Kernel Readouts (Wave Align, H(w), FDI, etc.): The live scores of each individual kernel. This allows you to see why the Field Score is what it is. A high Field Score with all components in agreement (all green or red) is a state of High Coherence and represents a high-quality setup.
Market Context: Standard metrics like RSI and Volume for additional confluence.
Signals: The raw and adjusted confluence counts and the final, calculated probability scores for potential long and short entries.
Pattern: Shows the dominant candlestick pattern detected within the currently forming APEX range box and its calculated confidence percentage.
Chapter 4: Mastering the Controls - The Inputs Menu
Every parameter is a lever to fine-tune the IGMD engine.
📊 Wavelet Transform: Kernel ( Haar for sharp moves, db2 for smooth trends) and Scales (depth of analysis) let you tune the script's core microscope to your asset's personality.
📈 Hurst Exponent: The Window determines if you're assessing short-term or long-term market memory.
🔍 Fractal Dimension & ⚡ Entropy Volatility: Adjust the lookback windows to make these kernels more or less sensitive to recent price action. Always keep "Normalize by ATR" enabled for Entropy for consistent results.
🔄 Transfer Entropy: Driver lets you choose what causal force to measure (e.g., OBV, Volume, or even an external symbol like VIX). The throttle setting is a crucial performance tool, allowing you to balance precision with script speed.
⚡ Field Fusion • Weights: This is where you can customize the model's "brain." Increase the weights for the kernels that best align with your trading philosophy (e.g., w_hurst for trend followers, w_fdi for chop avoiders).
📊 Signal Engine: Mode offers presets from Conservative to Aggressive . Min Confluence sets your evidence threshold. Dynamic Confluence is a powerful feature that automatically adapts this threshold to the market regime.
🎨 Visuals & 📏 Support/Resistance: These inputs give you full control over the chart's appearance, allowing you to toggle every visual element for a setup that is as clean or as data-rich as you desire.
Chapter 5: Reading the Battlefield - On-Chart Visuals
Pattern Boxes (The Large Rectangles): These are not simple range boxes. They appear when the Field Score crosses a significance threshold, signaling a potential ignition point.
Color: The color reflects the dominant candlestick pattern that has occurred within that box's duration (e.g., green for Bull Engulf).
Label: Displays the dominant pattern, its duration in bars, and a calculated Confidence % based on field strength and pattern clarity.
Bar Pattern Boxes (The Small Boxes): If enabled, these highlight individual, significant candlestick patterns ( BE for Bull Engulf, H for Hammer) on a bar-by-bar basis.
Signal Markers (▲ and ▼): These appear only when the Signal Engine's criteria are all met. The number is the calculated Probability Score .
RR Rails (Dashed Lines): When a signal appears, these lines automatically plot the Entry, Stop Loss (based on ATR), and two Take Profit targets (based on Risk/Reward ratios). They dynamically break and disappear as price touches each level.
Support & Resistance Lines: Plots of the highest high ( Resistance ) and lowest low ( Support ) over a lookback, providing key structural levels.
Chapter 6: Development Philosophy & A Final Word
One single question: " What is the market really doing? " It represents a triumph of complexity, blending concepts from signal processing, chaos theory, and information theory into a cohesive framework. It is offered for educational and analytical purposes and does not constitute financial advice. Its goal is to elevate your analysis from interpreting flat shadows to measuring the rich, geometric reality of the market's information field.
As the great mathematician Benoit Mandelbrot , father of fractal geometry, noted:
"Clouds are not spheres, mountains are not cones, coastlines are not circles, and bark is not smooth, nor does lightning travel in a straight line."
Neither does the market. IGMD is a tool designed to navigate that beautiful, complex, and fractal reality.
— Dskyz, Trade with insight. Trade with anticipation.
52SIGNAL RECIPE Smart Money Detector : CME + Exchanges=================52SIGNAL RECIPE CME-Exchange Smart Money Detector=================
◆ Overview
The 52SIGNAL RECIPE CME-Exchange Smart Money Detector is an advanced technical indicator designed to identify institutional and smart money movements by analyzing and comparing futures markets across both CME and cryptocurrency exchanges. This powerful tool detects coordinated buying and selling patterns that often precede significant price movements, giving traders an edge in anticipating market direction.
What makes this indicator unique is its cross-market verification approach. By requiring confirmation from both CME Bitcoin futures (dominated by institutional players) and crypto exchange futures (with broader market participation), it significantly reduces false signals and identifies high-probability smart money footprints that typically lead market movements.
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◆ Key Features
• Dual Market Confirmation: Simultaneously analyzes both CME Bitcoin futures and exchange futures charts to identify synchronized smart money activity
• Smart Volume Analysis: Uses advanced algorithms to separate buying and selling volume based on candle structure and price action
• Energy Wave Visualization: Displays smart money signals as intuitive energy waves with varying sizes reflecting signal strength
• Strength Rating System: Quantifies signal strength on a 0-100% scale, with multiple visualization levels (10%+, 40%+, 60%+, 80%+)
• Candlestick Pattern Integration: Incorporates bullish/bearish candle formations to enhance signal reliability
• Volume Spike Detection: Identifies abnormal volume increases that often accompany smart money positioning
• Trend Context Analysis: Evaluates signals in relation to current market trend for higher probability setups
• Dynamic Strength Calculation: Uses a multi-factor model considering volume ratio, buying/selling imbalance, candle structure, and trend alignment
• Transparent Signal Labeling: Displays precise strength percentage values with each signal for clear decision-making
• Real-time Institutional Flow Monitor: Tracks the footprints of large players across both regulated (CME) and crypto exchange markets
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◆ Understanding Signal Types
■ Buy Signal Energy Waves (Green)
• Definition: Detected when significant buying pressure appears simultaneously on both CME and exchange futures, typically on bearish candles
• Visual Appearance: Green circular waves below price bars, with size/opacity increasing with signal strength
• Market Interpretation: Indicates institutional buying interest even as price is declining, often preceding bullish reversals
• Signal Strength Factors:
▶ Higher buying volume relative to selling volume
▶ Above-average total volume
▶ Lower wicks on bearish candles
▶ Appearance at key support levels
▶ Coinciding with oversold conditions
■ Sell Signal Energy Waves (Red)
• Definition: Detected when significant selling pressure appears simultaneously on both CME and exchange futures, typically on bullish candles
• Visual Appearance: Red circular waves above price bars, with size/opacity increasing with signal strength
• Market Interpretation: Indicates institutional selling interest even as price is rising, often preceding bearish reversals
• Signal Strength Factors:
▶ Higher selling volume relative to buying volume
▶ Above-average total volume
▶ Upper wicks on bullish candles
▶ Appearance at key resistance levels
▶ Coinciding with overbought conditions
─────────────────────────────────────
◆ Signal Strength Understanding
■ The Four Strength Levels
• Level 1 (10-39%): Initial Detection
▶ Visual: Smallest energy wave
▶ Meaning: Early smart money positioning detected
▶ Usage: Early warning, prepare for possible setup
• Level 2 (40-59%): Moderate Strength
▶ Visual: Medium-small energy wave
▶ Meaning: Clearer institutional positioning
▶ Usage: Begin position planning, watch for confirmation
• Level 3 (60-79%): Strong Signal
▶ Visual: Medium-large energy wave
▶ Meaning: Significant smart money footprint
▶ Usage: High-probability setup forming, consider entry
• Level 4 (80-100%): Exceptional Strength
▶ Visual: Largest energy wave
▶ Meaning: Powerful institutional movement confirmed
▶ Usage: Highest probability setup, strong conviction entry point
■ Understanding Signal Strength Calculation
• Volume Component (0-50 points):
▶ Measures how current volume compares to recent average
▶ Maximum points when volume is 2x or higher than average
• Buy/Sell Ratio Component (0-50 points):
▶ Measures imbalance between buying and selling pressure
▶ Maximum points when ratio exceeds predefined multiplier threshold
• Advanced Weighting Factors:
▶ Candle Structure: Body size, wick length, and orientation
▶ Trend Alignment: Signal relationship to current trend
▶ Volume Spike: Abnormal volume increase detection
▶ Cross-Market Confirmation: Strength of signal alignment between CME and exchange
─────────────────────────────────────
◆ Practical Trading Applications
■ Reversal Trading Strategy
• Buy Signal Application:
▶ Setup: Strong buy energy wave (60%+) on a bearish candle
▶ Entry: After confirmation candle following the signal
▶ Stop Loss: Below recent low or 1 ATR below entry
▶ Take Profit: Previous resistance or 1:2 risk-reward minimum
▶ Enhancers: Signal occurring at support zone, oversold conditions, or trend line tests
• Sell Signal Application:
▶ Setup: Strong sell energy wave (60%+) on a bullish candle
▶ Entry: After confirmation candle following the signal
▶ Stop Loss: Above recent high or 1 ATR above entry
▶ Take Profit: Previous support or 1:2 risk-reward minimum
▶ Enhancers: Signal occurring at resistance zone, overbought conditions, or trend line tests
■ Trend Continuation Strategy
• During Uptrends:
▶ Focus on buy signals that appear during pullbacks
▶ Higher probability when signals occur at key moving averages or support levels
▶ Enter on strength when price shows signs of resuming the uptrend
• During Downtrends:
▶ Focus on sell signals that appear during relief rallies
▶ Higher probability when signals occur at key moving averages or resistance levels
▶ Enter on strength when price shows signs of resuming the downtrend
■ Multiple Timeframe Approach
• Signal Confirmation Across Timeframes:
▶ Major signals on higher timeframes (4H, daily) provide strategic direction
▶ Signals on lower timeframes (15m, 1H) offer tactical entry points
▶ Highest probability setups occur when signals align across multiple timeframes
• Signal Clustering:
▶ Multiple signals in the same price area significantly increase probability
▶ Look for areas where both buy and sell signals have appeared, indicating battleground zones
▶ The most recent signal direction often wins these battles
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◆ Technical Foundation
■ Why Cross-Market Confirmation Matters
• Institutional Participation:
▶ CME Bitcoin futures are dominated by regulated institutional investors
▶ Crypto exchange futures include both retail and institutional players
▶ When both markets show the same smart money pattern, the signal reliability increases dramatically
• Market Inefficiency Exploitation:
▶ Large players often position across multiple venues to minimize market impact
▶ This coordinated activity creates detectable footprints when analyzed correctly
▶ Cross-market confirmation helps filter out market noise and isolate true smart money movements
■ Smart Volume Calculation Methodology
• Price-Volume Relationship Analysis:
▶ Uses candle structure to estimate buying vs. selling volume
▶ Buying volume = Total volume × (Close - Low) / (High - Low)
▶ Selling volume = Total volume × (High - Close) / (High - Low)
• Signal Triggering Logic:
▶ Buy signal: When buying volume exceeds selling volume by multiplier factor
▶ Sell signal: When selling volume exceeds buying volume by multiplier factor
▶ Both conditions must be met simultaneously on CME and exchange futures
• Advanced Pattern Recognition:
▶ Evaluates candle body-to-range ratio for signal quality
▶ Analyzes wick length and position for additional confirmation
▶ Considers recent highs/lows to detect potential turning points
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◆ Indicator Settings Guide
■ Main Settings
• CME Bitcoin Futures Symbol:
▶ Default: CME:BTC1!
▶ Purpose: Sets the CME futures contract to analyze alongside current chart
• Buy/Sell Volume Multiplier:
▶ Default: 3.0
▶ Range: 1.0-10.0
▶ Purpose: Determines how much buying volume must exceed selling volume (or vice versa) to trigger a signal
▶ Higher values = fewer but stronger signals
▶ Lower values = more signals but potentially lower reliability
■ Volume Filter Settings
• Enable Volume Filter:
▶ Default: Enabled
▶ Purpose: When enabled, only considers candles with above-threshold volume
• Volume Average Period:
▶ Default: 20 candles
▶ Range: 5-200 candles
▶ Purpose: Sets the lookback period for calculating average volume
• Volume Threshold:
▶ Default: 150%
▶ Range: 10%-500%
▶ Purpose: Minimum volume percentage (of average) required for signal consideration
▶ Higher values focus on only the most significant volume spikes
■ Signal Visualization
• Show Signal Strength Value:
▶ Default: Enabled
▶ Purpose: Displays the exact percentage strength value with each signal
• Energy Wave Colors:
▶ Buy Energy Wave: Green (#00ff80)
▶ Sell Energy Wave: Red (#ff4040)
▶ Purpose: Customize the appearance of energy waves for visual preference
■ Advanced Settings
• Use Advanced Strength Calculation:
▶ Default: Enabled
▶ Purpose: When enabled, uses the full multi-factor model for signal strength
▶ When disabled, uses only basic volume and ratio factors
─────────────────────────────────────
◆ Synergy with Other Indicators
• Support/Resistance Levels:
▶ Smart money signals occurring at key support/resistance significantly increase reliability
▶ Particularly powerful when signals appear at tested price levels
• Moving Averages:
▶ Signals near key moving averages (50MA, 200MA) often indicate institutional interest
▶ Moving average crosses combined with smart money signals create high-probability setups
• RSI/Momentum Indicators:
▶ Buy signals in oversold conditions increase probability of successful reversal
▶ Sell signals in overbought conditions increase probability of successful reversal
• Volume Profile:
▶ Signals occurring at high volume nodes often indicate significant turning points
▶ Low volume nodes between high volume areas can act as acceleration zones after signal triggers
• Market Structure:
▶ Smart money signals that break key market structure levels (higher highs/lows or lower highs/lows) are particularly significant
▶ Can signal the early stages of trend changes when aligned with structure breaks
─────────────────────────────────────
◆ Conclusion
The 52SIGNAL RECIPE CME-Exchange Smart Money Detector provides traders with a powerful edge by revealing institutional positioning across both regulated futures and crypto exchange markets. By requiring synchronized signals from both venues, it cuts through market noise to identify the most reliable smart money footprints.
What sets this indicator apart is its sophisticated cross-market verification system. Rather than relying on signals from a single market, it only triggers when both CME and exchange futures display the same smart money pattern simultaneously. This approach dramatically reduces false signals and highlights truly significant institutional activity.
The intuitive energy wave visualization system makes it easy to spot signals of varying strength, while the transparent percentage rating allows for objective assessment of each opportunity. By focusing on these dual-confirmed smart money movements, traders can position themselves alongside institutional players rather than against them.
Remember that the most powerful signals typically appear at key market junctures, often before significant price movements. By incorporating this indicator into your trading approach, you gain insight into institutional positioning that can help anticipate market direction with greater confidence.
─────────────────────────────────────
※ Disclaimer: Like all trading tools, the CME-Exchange Smart Money Detector should be used as a supplementary indicator and not relied upon exclusively for trading decisions. Past patterns of institutional behavior may not guarantee future market movements. Always employ appropriate risk management strategies in your trading.
================52SIGNAL RECIPE CME-Exchange Smart Money Detector==================
◆ 개요
52SIGNAL RECIPE CME-Exchange Smart Money Detector는 CME와 암호화폐 거래소의 선물 시장을 동시에 분석하여 기관 및 스마트 머니의 움직임을 포착하는 고급 기술적 지표입니다. 이 강력한 도구는 주요 가격 움직임에 선행하는 조직적인 매수 및 매도 패턴을 감지하여 트레이더들에게 시장 방향 예측에 유리한 정보를 제공합니다.
이 지표의 독보적인 특징은 교차 시장 검증 접근법에 있습니다. CME 비트코인 선물(기관 투자자 중심)과 암호화폐 거래소 선물(광범위한 시장 참여자) 모두에서 확인을 요구함으로써, 허위 신호를 크게 줄이고 일반적으로 시장 움직임을 선도하는 고확률 스마트 머니 흔적을 식별합니다.
─────────────────────────────────────
◆ 주요 특징
• 듀얼 마켓 확인: CME 비트코인 선물과 거래소 선물 차트를 동시에 분석하여 동기화된 스마트 머니 활동 식별
• 스마트 볼륨 분석: 캔들 구조와 가격 행동을 기반으로 매수 및 매도 볼륨을 분리하는 고급 알고리즘 사용
• 에너지 파동 시각화: 스마트 머니 신호를 신호 강도를 반영하는 다양한 크기의 직관적인 에너지 파동으로 표시
• 강도 평가 시스템: 신호 강도를 0-100% 척도로 수치화하고 여러 시각화 레벨(10%+, 40%+, 60%+, 80%+) 제공
• 캔들스틱 패턴 통합: 신호 신뢰성을 높이기 위해 상승/하락 캔들 형성을 분석에 통합
• 볼륨 스파이크 감지: 스마트 머니 포지셔닝을 동반하는 비정상적인 볼륨 증가 식별
• 추세 맥락 분석: 현재 시장 추세와 관련하여 신호를 평가하여 높은 확률의 설정 제공
• 동적 강도 계산: 볼륨 비율, 매수/매도 불균형, 캔들 구조 및 추세 일치도를 고려하는 다중 요소 모델 사용
• 투명한 신호 라벨링: 명확한 의사 결정을 위해 각 신호와 함께 정확한 강도 백분율 값 표시
• 실시간 기관 자금 흐름 모니터: 규제된(CME) 시장과 암호화폐 거래소 시장 모두에서 대형 플레이어의 흔적 추적
─────────────────────────────────────
◆ 신호 유형 이해하기
■ 매수 신호 에너지 파동 (녹색)
• 정의: 일반적으로 하락 캔들에서 CME와 거래소 선물 모두에서 동시에 상당한 매수 압력이 감지될 때 발생
• 시각적 모습: 가격 바 아래에 녹색 원형 파동으로 표시되며, 신호 강도에 따라 크기/불투명도 증가
• 시장 해석: 가격이 하락하는 동안에도 기관의 매수 관심이 있음을 나타내며, 종종 상승 반전에 선행
• 신호 강도 요소:
▶ 매도 볼륨 대비 높은 매수 볼륨
▶ 평균 이상의 총 거래량
▶ 하락 캔들의 아래 꼬리
▶ 주요 지지 수준에서의 출현
▶ 과매도 조건과 일치
■ 매도 신호 에너지 파동 (적색)
• 정의: 일반적으로 상승 캔들에서 CME와 거래소 선물 모두에서 동시에 상당한 매도 압력이 감지될 때 발생
• 시각적 모습: 가격 바 위에 적색 원형 파동으로 표시되며, 신호 강도에 따라 크기/불투명도 증가
• 시장 해석: 가격이 상승하는 동안에도 기관의 매도 관심이 있음을 나타내며, 종종 하락 반전에 선행
• 신호 강도 요소:
▶ 매수 볼륨 대비 높은 매도 볼륨
▶ 평균 이상의 총 거래량
▶ 상승 캔들의 위 꼬리
▶ 주요 저항 수준에서의 출현
▶ 과매수 조건과 일치
─────────────────────────────────────
◆ 신호 강도 이해하기
■ 네 가지 강도 레벨
• 레벨 1 (10-39%): 초기 감지
▶ 시각적: 가장 작은 에너지 파동
▶ 의미: 초기 스마트 머니 포지셔닝 감지
▶ 활용: 초기 경고, 가능한 설정 준비
• 레벨 2 (40-59%): 중간 강도
▶ 시각적: 중간-작은 에너지 파동
▶ 의미: 더 명확한 기관 포지셔닝
▶ 활용: 포지션 계획 시작, 확인 대기
• 레벨 3 (60-79%): 강한 신호
▶ 시각적: 중간-큰 에너지 파동
▶ 의미: 중요한 스마트 머니 흔적
▶ 활용: 고확률 설정 형성, 진입 고려
• 레벨 4 (80-100%): 예외적 강도
▶ 시각적: 가장 큰 에너지 파동
▶ 의미: 강력한 기관 움직임 확인
▶ 활용: 최고 확률 설정, 강한 확신의 진입 지점
■ 신호 강도 계산 이해하기
• 볼륨 구성 요소 (0-50 포인트):
▶ 현재 볼륨이 최근 평균과 비교하여 얼마나 높은지 측정
▶ 볼륨이 평균보다 2배 이상 높을 때 최대 포인트 부여
• 매수/매도 비율 구성 요소 (0-50 포인트):
▶ 매수와 매도 압력 간의 불균형 측정
▶ 비율이 미리 정의된 배율 임계값을 초과할 때 최대 포인트 부여
• 고급 가중치 요소:
▶ 캔들 구조: 몸통 크기, 꼬리 길이 및 방향
▶ 추세 일치: 현재 추세와의 신호 관계
▶ 볼륨 스파이크: 비정상적인 볼륨 증가 감지
▶ 교차 시장 확인: CME와 거래소 간 신호 일치 강도
─────────────────────────────────────
◆ 실전 트레이딩 응용
■ 반전 트레이딩 전략
• 매수 신호 응용:
▶ 설정: 하락 캔들에서 강한 매수 에너지 파동(60%+)
▶ 진입: 신호 이후 확인 캔들 이후
▶ 손절: 최근 저점 아래 또는 진입점 아래 1 ATR
▶ 이익실현: 이전 저항 또는 최소 1:2 리스크-리워드
▶ 강화 요소: 지지 구역, 과매도 조건 또는 추세선 테스트에서 발생하는 신호
• 매도 신호 응용:
▶ 설정: 상승 캔들에서 강한 매도 에너지 파동(60%+)
▶ 진입: 신호 이후 확인 캔들 이후
▶ 손절: 최근 고점 위 또는 진입점 위 1 ATR
▶ 이익실현: 이전 지지 또는 최소 1:2 리스크-리워드
▶ 강화 요소: 저항 구역, 과매수 조건 또는 추세선 테스트에서 발생하는 신호
■ 추세 지속 전략
• 상승 추세 중:
▶ 조정 중에 나타나는 매수 신호에 집중
▶ 주요 이동평균선이나 지지 수준에서 신호가 발생할 때 확률이 높음
▶ 가격이 상승 추세를 재개할 징후를 보일 때 강도에 맞춰 진입
• 하락 추세 중:
▶ 일시적 반등 중에 나타나는 매도 신호에 집중
▶ 주요 이동평균선이나 저항 수준에서 신호가 발생할 때 확률이 높음
▶ 가격이 하락 추세를 재개할 징후를 보일 때 강도에 맞춰 진입
■ 다중 시간프레임 접근법
• 다양한 시간프레임에서의 신호 확인:
▶ 상위 시간프레임(4시간, 일봉)의 주요 신호는 전략적 방향 제공
▶ 하위 시간프레임(15분, 1시간)의 신호는 전술적 진입 지점 제공
▶ 여러 시간프레임에서 신호가 일치할 때 가장 높은 확률의 설정 발생
• 신호 클러스터링:
▶ 동일한 가격 영역에서 여러 신호가 발생하면 확률이 크게 증가
▶ 매수와 매도 신호가 모두 나타난 영역을 찾아 전투 구역 식별
▶ 이러한 전투에서는 대개 가장 최근의 신호 방향이 우세
─────────────────────────────────────
◆ 기술적 기반
■ 교차 시장 확인이 중요한 이유
• 기관 참여:
▶ CME 비트코인 선물은 규제된 기관 투자자가 주도
▶ 암호화폐 거래소 선물은 소매 및 기관 플레이어 모두 포함
▶ 두 시장이 동일한 스마트 머니 패턴을 보일 때 신호 신뢰성이 크게 증가
• 시장 비효율성 활용:
▶ 대형 플레이어들은 시장 영향을 최소화하기 위해 여러 거래소에 걸쳐 포지션을 취하는 경우가 많음
▶ 이러한 조직적인 활동은 올바르게 분석할 때 감지 가능한 흔적을 남김
▶ 교차 시장 확인은 시장 노이즈를 필터링하고 진정한 스마트 머니 움직임을 분리하는 데 도움
■ 스마트 볼륨 계산 방법론
• 가격-볼륨 관계 분석:
▶ 캔들 구조를 사용하여 매수 대 매도 볼륨 추정
▶ 매수 볼륨 = 총 볼륨 × (종가 - 저가) / (고가 - 저가)
▶ 매도 볼륨 = 총 볼륨 × (고가 - 종가) / (고가 - 저가)
• 신호 트리거 로직:
▶ 매수 신호: 매수 볼륨이 매도 볼륨을 배율 요소만큼 초과할 때
▶ 매도 신호: 매도 볼륨이 매수 볼륨을 배율 요소만큼 초과할 때
▶ 두 조건 모두 CME와 거래소 선물에서 동시에 충족되어야 함
• 고급 패턴 인식:
▶ 신호 품질을 위한 캔들 몸통-범위 비율 평가
▶ 추가 확인을 위한 꼬리 길이 및 위치 분석
▶ 잠재적 전환점을 감지하기 위해 최근 고점/저점 고려
─────────────────────────────────────
◆ 지표 설정 가이드
■ 주요 설정
• CME 비트코인 선물 심볼:
▶ 기본값: CME:BTC1!
▶ 목적: 현재 차트와 함께 분석할 CME 선물 계약 설정
• 매수/매도 볼륨 배율:
▶ 기본값: 3.0
▶ 범위: 1.0-10.0
▶ 목적: 신호를 트리거하기 위해 매수 볼륨이 매도 볼륨을 얼마나 초과해야 하는지(또는 그 반대) 결정
▶ 높은 값 = 적지만 더 강한 신호
▶ 낮은 값 = 더 많은 신호지만 잠재적으로 낮은 신뢰성
■ 볼륨 필터 설정
• 볼륨 필터 활성화:
▶ 기본값: 활성화됨
▶ 목적: 활성화되면 임계값 이상의 볼륨을 가진 캔들만 고려
• 볼륨 평균 기간:
▶ 기본값: 20 캔들
▶ 범위: 5-200 캔들
▶ 목적: 평균 볼륨 계산을 위한 룩백 기간 설정
• 볼륨 임계값:
▶ 기본값: 150%
▶ 범위: 10%-500%
▶ 목적: 신호 고려에 필요한 최소 볼륨 백분율(평균 대비)
▶ 높은 값은 가장 중요한 볼륨 스파이크에만 집중
■ 신호 시각화
• 신호 강도 값 표시:
▶ 기본값: 활성화됨
▶ 목적: 각 신호와 함께 정확한 백분율 강도 값 표시
• 에너지 파동 색상:
▶ 매수 에너지 파동: 녹색(#00ff80)
▶ 매도 에너지 파동: 적색(#ff4040)
▶ 목적: 시각적 선호도에 맞게 에너지 파동의 모양 사용자 정의
■ 고급 설정
• 고급 강도 계산 사용:
▶ 기본값: 활성화됨
▶ 목적: 활성화되면 신호 강도에 전체 다중 요소 모델 사용
▶ 비활성화되면 기본 볼륨 및 비율 요소만 사용
─────────────────────────────────────
◆ 다른 지표와의 시너지
• 지지/저항 레벨:
▶ 주요 지지/저항에서 발생하는 스마트 머니 신호는 신뢰성을 크게 높임
▶ 특히 테스트된 가격 레벨에서 신호가 나타날 때 강력함
• 이동평균선:
▶ 주요 이동평균선(50MA, 200MA) 근처의 신호는 종종 기관의 관심을 나타냄
▶ 이동평균선 교차와 스마트 머니 신호의 조합은 고확률 설정 생성
• RSI/모멘텀 지표:
▶ 과매도 조건에서의 매수 신호는 성공적인 반전 확률 증가
▶ 과매수 조건에서의 매도 신호는 성공적인 반전 확률 증가
• 볼륨 프로파일:
▶ 높은 볼륨 노드에서 발생하는 신호는 종종 중요한 전환점을 나타냄
▶ 높은 볼륨 영역 사이의 낮은 볼륨 노드는 신호 트리거 후 가속 구간으로 작용할 수 있음
• 시장 구조:
▶ 주요 시장 구조 레벨(높은 고점/저점 또는 낮은 고점/저점)을 깨는 스마트 머니 신호는 특히 중요
▶ 구조 깨짐과 일치할 때 추세 변화의 초기 단계를 알릴 수 있음
─────────────────────────────────────
◆ 결론
52SIGNAL RECIPE CME-Exchange Smart Money Detector는 규제된 선물 시장과 암호화폐 거래소 시장 모두에서 기관의 포지셔닝을 드러냄으로써 트레이더에게 강력한 우위를 제공합니다. 두 거래소에서 동기화된 신호를 요구함으로써, 시장 노이즈를 제거하고 가장 신뢰할 수 있는 스마트 머니 흔적을 식별합니다.
이 지표를 차별화하는 것은 정교한 교차 시장 검증 시스템입니다. 단일 시장의 신호에 의존하는 대신, CME와 거래소 선물 모두가 동시에 동일한 스마트 머니 패턴을 표시할 때만 트리거됩니다. 이 접근 방식은 허위 신호를 크게 줄이고 진정으로 중요한 기관 활동을 강조합니다.
직관적인 에너지 파동 시각화 시스템을 통해 다양한 강도의 신호를 쉽게 발견할 수 있으며, 투명한 백분율 평가를 통해 각 기회를 객관적으로 평가할 수 있습니다. 이러한 이중 확인된 스마트 머니 움직임에 집중함으로써, 트레이더는 기관 참가자들에 대항하기보다는 그들과 함께 포지션을 취할 수 있습니다.
가장 강력한 신호는 일반적으로 주요 시장 변곡점에서, 종종 중요한 가격 움직임 이전에 나타난다는 점을 기억하세요. 이 지표를 트레이딩 접근법에 통합함으로써, 시장 방향을 더 높은 확신으로 예측하는 데 도움이 되는 기관 포지셔닝에 대한 통찰력을 얻을 수 있습니다.
─────────────────────────────────────
※ 면책 조항: 모든 트레이딩 도구와 마찬가지로, CME-Exchange Smart Money Detector는 보조 지표로 사용되어야 하며 트레이딩 결정을 전적으로 의존해서는 안 됩니다. 과거의 기관 행동 패턴이 미래 시장 움직임을 보장하지는 않습니다. 항상 적절한 리스크 관리 전략을 트레이딩에 사용하세요.
[Excalibur] Ehlers AutoCorrelation Periodogram ModifiedKeep your coins folks, I don't need them, don't want them. If you wish be generous, I do hope that charitable peoples worldwide with surplus food stocks may consider stocking local food banks before stuffing monetary bank vaults, for the crusade of remedying the needs of less than fortunate children, parents, elderly, homeless veterans, and everyone else who deserves nutritional sustenance for the soul.
DEDICATION:
This script is dedicated to the memory of Nikolai Dmitriyevich Kondratiev (Никола́й Дми́триевич Кондра́тьев) as tribute for being a pioneering economist and statistician, paving the way for modern econometrics by advocation of rigorous and empirical methodologies. One of his most substantial contributions to the study of business cycle theory include a revolutionary hypothesis recognizing the existence of dynamic cycle-like phenomenon inherent to economies that are characterized by distinct phases of expansion, stagnation, recession and recovery, what we now know as "Kondratiev Waves" (K-waves). Kondratiev was one of the first economists to recognize the vital significance of applying quantitative analysis on empirical data to evaluate economic dynamics by means of statistical methods. His understanding was that conceptual models alone were insufficient to adequately interpret real-world economic conditions, and that sophisticated analysis was necessary to better comprehend the nature of trending/cycling economic behaviors. Additionally, he recognized prosperous economic cycles were predominantly driven by a combination of technological innovations and infrastructure investments that resulted in profound implications for economic growth and development.
I will mention this... nation's economies MUST be supported and defended to continuously evolve incrementally in order to flourish in perpetuity OR suffer through eras with lasting ramifications of societal stagnation and implosion.
Analogous to the realm of economics, aperiodic cycles/frequencies, both enduring and ephemeral, do exist in all facets of life, every second of every day. To name a few that any blind man can naturally see are: heartbeat (cardiac cycles), respiration rates, circadian rhythms of sleep, powerful magnetic solar cycles, seasonal cycles, lunar cycles, weather patterns, vegetative growth cycles, and ocean waves. Do not pretend for one second that these basic aforementioned examples do not affect business cycle fluctuations in minuscule and monumental ways hour to hour, day to day, season to season, year to year, and decade to decade in every nation on the planet. Kondratiev's original seminal theories in macroeconomics from nearly a century ago have proven remarkably prescient with many of his antiquated elementary observations/notions/hypotheses in macroeconomics being scholastically studied and topically researched further. Therefore, I am compelled to honor and recognize his statistical insight and foresight.
If only.. Kondratiev could hold a pocket sized computer in the cup of both hands bearing the TradingView logo and platform services, I truly believe he would be amazed in marvelous delight with a GARGANTUAN smile on his face.
INTRODUCTION:
Firstly, this is NOT technically speaking an indicator like most others. I would describe it as an advanced cycle period detector to obtain market data spectral estimates with low latency and moderate frequency resolution. Developers can take advantage of this detector by creating scripts that utilize a "Dominant Cycle Source" input to adaptively govern algorithms. Be forewarned, I would only recommend this for advanced developers, not novice code dabbling. Although, there is some Pine wizardry introduced here for novice Pine enthusiasts to witness and learn from. AI did describe the code into one super-crunched sentence as, "a rare feat of exceptionally formatted code masterfully balancing visual clarity, precision, and complexity to provide immense educational value for both programming newcomers and expert Pine coders alike."
Understand all of the above aforementioned? Buckle up and proceed for a lengthy read of verbose complexity...
This is my enhanced and heavily modified version of autocorrelation periodogram (ACP) for Pine Script v5.0. It was originally devised by the mathemagician John Ehlers for detecting dominant cycles (frequencies) in an asset's price action. I have been sitting on code similar to this for a long time, but I decided to unleash the advanced code with my fashion. Originally Ehlers released this with multiple versions, one in a 2016 TASC article and the other in his last published 2013 book "Cycle Analytics for Traders", chapter 8. He wasn't joking about "concepts of advanced technical trading" and ACP is nowhere near to his most intimidating and ingenious calculations in code. I will say the book goes into many finer details about the original periodogram, so if you wish to delve into even more elaborate info regarding Ehlers' original ACP form AND how you may adapt algorithms, you'll have to obtain one. Note to reader, comparing Ehlers' original code to my chimeric code embracing the "Power of Pine", you will notice they have little resemblance.
What you see is a new species of autocorrelation periodogram combining Ehlers' innovation with my fascinations of what ACP could be in a Pine package. One other intention of this script's code is to pay homage to Ehlers' lifelong works. Like Kondratiev, Ehlers is also a hardcore cycle enthusiast. I intend to carry on the fire Ehlers envisioned and I believe that is literally displayed here as a pleasant "fiery" example endowed with Pine. With that said, I tried to make the code as computationally efficient as possible, without going into dozens of more crazy lines of code to speed things up even more. There's also a few creative modifications I made by making alterations to the originating formulas that I felt were improvements, one of them being lag reduction. By recently questioning every single thing I thought I knew about ACP, combined with the accumulation of my current knowledge base, this is the innovative revision I came up with. I could have improved it more but decided not to mind thrash too many TV members, maybe later...
I am now confident Pine should have adequate overhead left over to attach various indicators to the dominant cycle via input.source(). TV, I apologize in advance if in the future a server cluster combusts into a raging inferno... Coders, be fully prepared to build entire algorithms from pure raw code, because not all of the built-in Pine functions fully support dynamic periods (e.g. length=ANYTHING). Many of them do, as this was requested and granted a while ago, but some functions are just inherently finicky due to implementation combinations and MUST be emulated via raw code. I would imagine some comprehensive library or numerous authored scripts have portions of raw code for Pine built-ins some where on TV if you look diligently enough.
Notice: Unfortunately, I will not provide any integration support into member's projects at all. I have my own projects that require way too much of my day already. While I was refactoring my life (forgoing many other "important" endeavors) in the early half of 2023, I primarily focused on this code over and over in my surplus time. During that same time I was working on other innovations that are far above and beyond what this code is. I hope you understand.
The best way programmatically may be to incorporate this code into your private Pine project directly, after brutal testing of course, but that may be too challenging for many in early development. Being able to see the periodogram is also beneficial, so input sourcing may be the "better" avenue to tether portions of the dominant cycle to algorithms. Unique indication being able to utilize the dominantCycle may be advantageous when tethering this script to those algorithms. The easiest way is to manually set your indicators to what ACP recognizes as the dominant cycle, but that's actually not considered dynamic real time adaption of an indicator. Different indicators may need a proportion of the dominantCycle, say half it's value, while others may need the full value of it. That's up to you to figure that out in practice. Sourcing one or more custom indicators dynamically to one detector's dominantCycle may require code like this: `int sourceDC = int(math.max(6, math.min(49, input.source(close, "Dominant Cycle Source"))))`. Keep in mind, some algos can use a float, while algos with a for loop require an integer.
I have witnessed a few attempts by talented TV members for a Pine based autocorrelation periodogram, but not in this caliber. Trust me, coding ACP is no ordinary task to accomplish in Pine and modifying it blessed with applicable improvements is even more challenging. For over 4 years, I have been slowly improving this code here and there randomly. It is beautiful just like a real flame, but... this one can still burn you! My mind was fried to charcoal black a few times wrestling with it in the distant past. My very first attempt at translating ACP was a month long endeavor because PSv3 simply didn't have arrays back then. Anyways, this is ACP with a newer engine, I hope you enjoy it. Any TV subscriber can utilize this code as they please. If you are capable of sufficiently using it properly, please use it wisely with intended good will. That is all I beg of you.
Lastly, you now see how I have rasterized my Pine with Ehlers' swami-like tech. Yep, this whole time I have been using hline() since PSv3, not plot(). Evidently, plot() still has a deficiency limited to only 32 plots when it comes to creating intense eye candy indicators, the last I checked. The use of hline() is the optimal choice for rasterizing Ehlers styled heatmaps. This does only contain two color schemes of the many I have formerly created, but that's all that is essentially needed for this gizmo. Anything else is generally for a spectacle or seeing how brutal Pine can be color treated. The real hurdle is being able to manipulate colors dynamically with Merlin like capabilities from multiple algo results. That's the true challenging part of these heatmap contraptions to obtain multi-colored "predator vision" level indication. You now have basic hline() food for thought empowerment to wield as you can imaginatively dream in Pine projects.
PERIODOGRAM UTILITY IN REAL WORLD SCENARIOS:
This code is a testament to the abilities that have yet to be fully realized with indication advancements. Periodograms, spectrograms, and heatmaps are a powerful tool with real-world applications in various fields such as financial markets, electrical engineering, astronomy, seismology, and neuro/medical applications. For instance, among these diverse fields, it may help traders and investors identify market cycles/periodicities in financial markets, support engineers in optimizing electrical or acoustic systems, aid astronomers in understanding celestial object attributes, assist seismologists with predicting earthquake risks, help medical researchers with neurological disorder identification, and detection of asymptomatic cardiovascular clotting in the vaxxed via full body thermography. In either field of study, technologies in likeness to periodograms may very well provide us with a better sliver of analysis beyond what was ever formerly invented. Periodograms can identify dominant cycles and frequency components in data, which may provide valuable insights and possibly provide better-informed decisions. By utilizing periodograms within aspects of market analytics, individuals and organizations can potentially refrain from making blinded decisions and leverage data-driven insights instead.
PERIODOGRAM INTERPRETATION:
The periodogram renders the power spectrum of a signal, with the y-axis representing the periodicity (frequencies/wavelengths) and the x-axis representing time. The y-axis is divided into periods, with each elevation representing a period. In this periodogram, the y-axis ranges from 6 at the very bottom to 49 at the top, with intermediate values in between, all indicating the power of the corresponding frequency component by color. The higher the position occurs on the y-axis, the longer the period or lower the frequency. The x-axis of the periodogram represents time and is divided into equal intervals, with each vertical column on the axis corresponding to the time interval when the signal was measured. The most recent values/colors are on the right side.
The intensity of the colors on the periodogram indicate the power level of the corresponding frequency or period. The fire color scheme is distinctly like the heat intensity from any casual flame witnessed in a small fire from a lighter, match, or camp fire. The most intense power would be indicated by the brightest of yellow, while the lowest power would be indicated by the darkest shade of red or just black. By analyzing the pattern of colors across different periods, one may gain insights into the dominant frequency components of the signal and visually identify recurring cycles/patterns of periodicity.
SETTINGS CONFIGURATIONS BRIEFLY EXPLAINED:
Source Options: These settings allow you to choose the data source for the analysis. Using the `Source` selection, you may tether to additional data streams (e.g. close, hlcc4, hl2), which also may include samples from any other indicator. For example, this could be my "Chirped Sine Wave Generator" script found in my member profile. By using the `SineWave` selection, you may analyze a theoretical sinusoidal wave with a user-defined period, something already incorporated into the code. The `SineWave` will be displayed over top of the periodogram.
Roofing Filter Options: These inputs control the range of the passband for ACP to analyze. Ehlers had two versions of his highpass filters for his releases, so I included an option for you to see the obvious difference when performing a comparison of both. You may choose between 1st and 2nd order high-pass filters.
Spectral Controls: These settings control the core functionality of the spectral analysis results. You can adjust the autocorrelation lag, adjust the level of smoothing for Fourier coefficients, and control the contrast/behavior of the heatmap displaying the power spectra. I provided two color schemes by checking or unchecking a checkbox.
Dominant Cycle Options: These settings allow you to customize the various types of dominant cycle values. You can choose between floating-point and integer values, and select the rounding method used to derive the final dominantCycle values. Also, you may control the level of smoothing applied to the dominant cycle values.
DOMINANT CYCLE VALUE SELECTIONS:
External to the acs() function, the code takes a dominant cycle value returned from acs() and changes its numeric form based on a specified type and form chosen within the indicator settings. The dominant cycle value can be represented as an integer or a decimal number, depending on the attached algorithm's requirements. For example, FIR filters will require an integer while many IIR filters can use a float. The float forms can be either rounded, smoothed, or floored. If the resulting value is desired to be an integer, it can be rounded up/down or just be in an integer form, depending on how your algorithm may utilize it.
AUTOCORRELATION SPECTRUM FUNCTION BASICALLY EXPLAINED:
In the beginning of the acs() code, the population of caches for precalculated angular frequency factors and smoothing coefficients occur. By precalculating these factors/coefs only once and then storing them in an array, the indicator can save time and computational resources when performing subsequent calculations that require them later.
In the following code block, the "Calculate AutoCorrelations" is calculated for each period within the passband width. The calculation involves numerous summations of values extracted from the roofing filter. Finally, a correlation values array is populated with the resulting values, which are normalized correlation coefficients.
Moving on to the next block of code, labeled "Decompose Fourier Components", Fourier decomposition is performed on the autocorrelation coefficients. It iterates this time through the applicable period range of 6 to 49, calculating the real and imaginary parts of the Fourier components. Frequencies 6 to 49 are the primary focus of interest for this periodogram. Using the precalculated angular frequency factors, the resulting real and imaginary parts are then utilized to calculate the spectral Fourier components, which are stored in an array for later use.
The next section of code smooths the noise ridden Fourier components between the periods of 6 and 49 with a selected filter. This species also employs numerous SuperSmoothers to condition noisy Fourier components. One of the big differences is Ehlers' versions used basic EMAs in this section of code. I decided to add SuperSmoothers.
The final sections of the acs() code determines the peak power component for normalization and then computes the dominant cycle period from the smoothed Fourier components. It first identifies a single spectral component with the highest power value and then assigns it as the peak power. Next, it normalizes the spectral components using the peak power value as a denominator. It then calculates the average dominant cycle period from the normalized spectral components using Ehlers' "Center of Gravity" calculation. Finally, the function returns the dominant cycle period along with the normalized spectral components for later external use to plot the periodogram.
POST SCRIPT:
Concluding, I have to acknowledge a newly found analyst for assistance that I couldn't receive from anywhere else. For one, Claude doesn't know much about Pine, is unfortunately color blind, and can't even see the Pine reference, but it was able to intuitively shred my code with laser precise realizations. Not only that, formulating and reformulating my description needed crucial finesse applied to it, and I couldn't have provided what you have read here without that artificial insight. Finding the right order of words to convey the complexity of ACP and the elaborate accompanying content was a daunting task. No code in my life has ever absorbed so much time and hard fricking work, than what you witness here, an ACP gem cut pristinely. I'm unveiling my version of ACP for an empowering cause, in the hopes a future global army of code wielders will tether it to highly functional computational contraptions they might possess. Here is ACP fully blessed poetically with the "Power of Pine" in sublime code. ENJOY!
