MathConstantsAtomicLibrary "MathConstantsAtomic"
Mathematical Constants
FineStructureConstant() Fine Structure Constant: alpha = e^2/4*Pi*e_0*h_bar*c_0 (2007 CODATA)
RydbergConstant() Rydberg Constant: R_infty = alpha^2*m_e*c_0/2*h (2007 CODATA)
BohrRadius() Bor Radius: a_0 = alpha/4*Pi*R_infty (2007 CODATA)
HartreeEnergy() Hartree Energy: E_h = 2*R_infty*h*c_0 (2007 CODATA)
QuantumOfCirculation() Quantum of Circulation: h/2*m_e (2007 CODATA)
FermiCouplingConstant() Fermi Coupling Constant: G_F/(h_bar*c_0)^3 (2007 CODATA)
WeakMixingAngle() Weak Mixin Angle: sin^2(theta_W) (2007 CODATA)
ElectronMass() Electron Mass: (2007 CODATA)
ElectronMassEnergyEquivalent() Electron Mass Energy Equivalent: (2007 CODATA)
ElectronMolarMass() Electron Molar Mass: (2007 CODATA)
ComptonWavelength() Electron Compton Wavelength: (2007 CODATA)
ClassicalElectronRadius() Classical Electron Radius: (2007 CODATA)
ThomsonCrossSection() Thomson Cross Section: (2002 CODATA)
ElectronMagneticMoment() Electron Magnetic Moment: (2007 CODATA)
ElectronGFactor() Electon G-Factor: (2007 CODATA)
MuonMass() Muon Mass: (2007 CODATA)
MuonMassEnegryEquivalent() Muon Mass Energy Equivalent: (2007 CODATA)
MuonMolarMass() Muon Molar Mass: (2007 CODATA)
MuonComptonWavelength() Muon Compton Wavelength: (2007 CODATA)
MuonMagneticMoment() Muon Magnetic Moment: (2007 CODATA)
MuonGFactor() Muon G-Factor: (2007 CODATA)
TauMass() Tau Mass: (2007 CODATA)
TauMassEnergyEquivalent() Tau Mass Energy Equivalent: (2007 CODATA)
TauMolarMass() Tau Molar Mass: (2007 CODATA)
TauComptonWavelength() Tau Compton Wavelength: (2007 CODATA)
ProtonMass() Proton Mass: (2007 CODATA)
ProtonMassEnergyEquivalent() Proton Mass Energy Equivalent: (2007 CODATA)
ProtonMolarMass() Proton Molar Mass: (2007 CODATA)
ProtonComptonWavelength() Proton Compton Wavelength: (2007 CODATA)
ProtonMagneticMoment() Proton Magnetic Moment: (2007 CODATA)
ProtonGFactor() Proton G-Factor: (2007 CODATA)
ShieldedProtonMagneticMoment() Proton Shielded Magnetic Moment: (2007 CODATA)
ProtonGyromagneticRatio() Proton Gyro-Magnetic Ratio: (2007 CODATA)
ShieldedProtonGyromagneticRatio() Proton Shielded Gyro-Magnetic Ratio: (2007 CODATA)
NeutronMass() Neutron Mass: (2007 CODATA)
NeutronMassEnegryEquivalent() Neutron Mass Energy Equivalent: (2007 CODATA)
NeutronMolarMass() Neutron Molar Mass: (2007 CODATA)
NeutronComptonWavelength() Neuron Compton Wavelength: (2007 CODATA)
NeutronMagneticMoment() Neutron Magnetic Moment: (2007 CODATA)
NeutronGFactor() Neutron G-Factor: (2007 CODATA)
NeutronGyromagneticRatio() Neutron Gyro-Magnetic Ratio: (2007 CODATA)
DeuteronMass() Deuteron Mass: (2007 CODATA)
DeuteronMassEnegryEquivalent() Deuteron Mass Energy Equivalent: (2007 CODATA)
DeuteronMolarMass() Deuteron Molar Mass: (2007 CODATA)
DeuteronMagneticMoment() Deuteron Magnetic Moment: (2007 CODATA)
HelionMass() Helion Mass: (2007 CODATA)
HelionMassEnegryEquivalent() Helion Mass Energy Equivalent: (2007 CODATA)
HelionMolarMass() Helion Molar Mass: (2007 CODATA)
Avogadro() Avogadro constant: (2010 CODATA)
Komut dosyalarını "wave" için ara
MTF VWAPA simple wavetrend oscillator based off WaveTrend Oscillator by @LazyBear to visualise 4 different timeframe vwap under 1 chart.
Timeframe can be changed in indicator settings in minutes. Unnecessary waves can be removed by unchecking said TF wave in Style settings.
Pragmatic risk managementINTRO
The indicator is calculating multiple moving averages on the value of price change %. It then combines the normalized (via arctan function) values into a single normalized value (via simple average).
The total error from the center of gravity and the angle in which the error is accumulating represented by 4 waves:
BLUE = Good for chance for price to go up
GREEN = Good chance for price to continue going up
ORANGE = Good chance for price to go down
RED = Good chance for price to continue going down
A full cycle of ORANGE\RED\BLUE\GREEN colors will ideally lead to the exact same cycle, if not, try to understand why.
NOTICE-
This indicator is calculating large time-windows so It can be heavy on your device. Tested on PC browser only.
My visual setup:
1. Add two indicators on-top of each other and merge their scales (It will help out later).
2. Zoom out price chart to see the maximum possible data.
3. Set different colors for both indicators for simple visual seperation.
4. Choose 2 different values, one as high as possible and one as low as possible.
(Possible - the indicator remains effective at distinguishing the cycle).
Manual calibration:
0. Select a fixed chart resolution (2H resolution minimum recommended).
1. Change the "mul2" parameter in ranges between 4-15 .
2. Observe the "Turning points" of price movement. (Typically when RED\GREEN are about to switch.)
2. Perform a segmentation of time slices and find cycles. No need to be exact!
3. Draw a square on price movement at place and color as the dominant wave currently inside the indicator.
This procedure should lead to a full price segmentation with easier anchoring.
[blackcat] L2 Ehlers Relative Vigor IndexLevel: 2
Background
John F. Ehlers introuced Relative Vigor Index in his "Cybernetic Analysis for Stocks and Futures" chapter 6 on 2004.
Function
Relative Vigor Index (RVI) uses concepts dating back over three decades and also uses modern filter and digital signal processing theory to realize those concepts as a practical and useful indicator. The RVI merges the old concepts with the new technologies. The basic idea of the RVI is that prices tend to close higher than
they open in up markets and tend to close lower than they open in down markets. The vigor of the move is thus established by where the prices reside at the end of the day. To normalize the index to the daily trading range, the change in price is divided by the maximum range of prices for the day.
The RVI is an oscillator, and we are therefore only concerned with the cycle modes of the market in its use. The sharpest rate of change for a cycle is at its midpoint. Therefore, in the ascending part of the cycle we would expect the difference between the close and open to be at a maximum. This is like a derivative in calculus, where the derivative of a sinewave produces a negative cosine wave. The derivative is therefore a waveform that leads the original sinewave by a quarter cycle. Also, from calculus, integration of a sinewave over a half-cycle period results in another sinewave delayed by a quarter cycle. Summing over a half cycle is basically the same as mathematically integrating, with the result that the waveshape of the sum is delayed by a quarter wavelength relative to the input. The net result of taking the differences and summing produces an oscillator output in phase with the cyclic component of the price. It is also possible to generate a leading function if the summation window is less than a half wavelength of the Dominant Cycle. If a cycle measurement is not available, you can sum the RVI components over a fixed default period. A nominal value of 8 is suggested because this is approximately half the period of most cycles of interest.
Key Signal
RVI ---> Relative Vigor Index fast line
Trigger ---> Relative Vigor Index 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 27th 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.
Momentum ArrowsThis simple indicators paints the Momentum based on Stochastic, RSI or WaveTrend onto the Price Chart by showing Green or Red arrows.
In the settings it can be selected which indicator is used, Stochastic is selected by default.
Length of the arrows is determined by the strength of the momentum:
Stochastic: Difference between D and K
RSI: Difference from RSI-50
WaveTrend: Difference between the Waves
(Thanks to @LazyBear for the WaveTrend inspiration)
PS:
If anyone has an idea how to conditionally change the color of the arrows, then please let me know - that would be the icing on the cake. Then it would be possible to indicate Overbought/Oversold levels with different colors.
Unfortunately it currently seems not to be possible to dynamically change the arrow colour.
WWV_LB pivotfix histogram jayy
This is a modification of LazyBear's WWV_LB which plots cumulative volume of waves. The reversal points are defined through relative closing prices. I made adjustments to the script to show waves turning on actual/true low or high pivots as opposed to the bar/candle identified in the LazyBear script. What I mean by that is that the actual/true low or high pivots are in fact the true WWV_LB pivots. The original WWV_LB script calculates cumulative volume from reversal confirmation bar to reversal confirmation bar as opposed to the true WWV_LB pivot bar to pivot bar. As such the waves can have slightly different start and end points. As such the cumulative volume can also be different from te WWV_LB script. This is because confirmation of a wave reversal can lag a few bars after the true reversal pivot bar. In the script notes, you will see the original key WWV_LB script lines that identify the true high or low pivots and confirm the wave direction has reversed. I have taken these lines from LazyBear's original script. I have included the LazyBear script within the script notes so that the original can be compared to what I have added/changed. Instead of "trendDetectionLength" I have inserted "Trend Detection Length". You can of course change the descriptor to what you wish by editing script line 33 to the original term or whatever you wish. You might also wish to set the default to the value "2" as per the original script. I have set the default to "3". This script should be used in conjunction with "WWV-LB zigzag pivot fix jayy" script which is shown on this screen for comparison.
Here is a link to the original LazyBear histogram script which can be used for comparison. The differences are subtle, however, the histograms will regularly be different by a bar or two:
The lowest panel has the original LazyBear WWV_LB script for comparison. All three scripts have been set to a Trend Detection Length of 3.jayy
Rate of Change HistogramExplanation of Modifications
Converting ROC to Histogram:
Original ROC: The ROC is calculated as roc = 100 * (source - source ) / source , plotted as a line oscillating around zero.
Modification: Instead of plotting roc as a line, it’s now plotted as a histogram using style=plot.style_columns. This makes the ROC values visually resemble the MACD histogram, with bars extending above or below the zero line based on momentum.
Applying MACD’s Four-Color Scheme:
Logic: The histogram’s color is determined by:
Above Zero (roc >= 0): Bright green (#26A69A) if ROC is rising (roc > roc ), light green (#B2DFDB) if falling (roc < roc ).
Below Zero (roc < 0): Bright red (#FF5252) if ROC is falling (roc < roc ), light red (#FFCDD2) if rising (roc > roc ).
Implementation: Used the exact color logic and hex codes from the MACD code, applied to the ROC histogram. This highlights momentum ebbs (falling ROC, fading waves) and flows (rising ROC, strengthening waves).
Removing Signal Line:
Unlike the previous attempt, no signal line is added. The histogram is purely the ROC value, ensuring it directly reflects price change momentum without additional smoothing, making it faster and more responsive to pulse waves, as you indicated ROC performs better than other oscillators.
Alert Conditions:
Added alerts to match the MACD’s logic, triggering when the ROC histogram crosses the zero line:
Rising to Falling: When roc >= 0 and roc < 0, signaling a potential wave peak (e.g., end of Wave 3 or C).
Falling to Rising: When roc <= 0 and roc > 0, indicating a potential wave bottom (e.g., start of Wave 1 or rebound).
These alerts help identify transitions in 3-4 wave pulse patterns.
Plotting:
Histogram: Plotted as columns (plot.style_columns) with the four-color scheme, directly representing ROC momentum.
Zero Line: Kept the gray zero line (#787B86) for reference, consistent with the MACD.
Removed ROC Line/Signal Line: Since you want the ROC to act as the histogram itself, no additional lines are plotted.
Inputs:
Retained the original length (default 9) and source (default close) inputs for consistency.
Removed signal-related inputs (e.g., signal_length, sma_signal) as they’re not needed for a pure ROC histogram.
How This ROC Histogram Works for Wave Pulses
Wave Alignment:
Above Zero (Bullish Momentum): Positive ROC bars indicate flows (e.g., impulse Waves 1, 3, or rebounds in Wave B/C). Bright green bars show accelerating momentum (strong pulses), while light green bars suggest fading momentum (potential wave tops).
Below Zero (Bearish Momentum): Negative ROC bars indicate ebbs (e.g., corrective Waves 2, 4, A, or C). Bright red bars show increasing bearish momentum (strong pullbacks), while light red bars suggest slowing declines (potential wave bottoms).
3-4 Wave Pulses:
In a 3-wave A-B-C correction: Wave A (down) shows bright red bars (falling ROC), Wave B (up) shows bright/light green bars (rising ROC), and Wave C (down) shifts back to red bars.
In a 4-wave consolidation: Alternating green/red bars highlight the rhythmic ebbs and flows as momentum oscillates.
Timing:
Zero-line crossovers mark wave transitions (e.g., from Wave 2 to Wave 3).
Color changes (e.g., bright to light green) signal momentum shifts within waves, helping identify pulse peaks/troughs.
Advantages Over MACD:
The ROC histogram is more responsive than the MACD histogram because ROC directly measures price change percentage, while MACD relies on moving average differences, which introduce lag. This makes the ROC histogram better for capturing rapid 3-4 wave pulses, as you noted.
Example Usage
For a stock with 3-4 wave pulses on a 5-minute chart:
Wave 1 (Flow): ROC rises above zero, histogram turns bright green (rising momentum), indicating a strong bullish pulse.
Wave 2 (Ebb): ROC falls below zero, histogram shifts to bright red (falling momentum), signaling a corrective pullback.
Wave 3 (Flow): ROC crosses back above zero, histogram becomes bright green again, confirming a powerful pulse.
Wave 4 (Ebb): ROC dips slightly, histogram turns light green (falling momentum above zero) or light red (rising momentum below zero), indicating consolidation.
Alerts trigger on zero-line crosses (e.g., from Wave 2 to Wave 3), helping time trades.
Settings Recommendations
Default (length=9): Works well for most time frames, balancing sensitivity and smoothness.
Intraday Pulses: Use length=5 or length=7 for faster signals on 5-minute or 15-minute charts.
Daily Charts: Try length=12 or length=14 for broader wave cycles.
Testing: Apply to a stock with clear wave patterns (e.g., tech stocks like AAPL or TSLA) and adjust length to match the pulse frequency you observe.
Notes
Confirmation: Pair the ROC histogram with price action (e.g., Fibonacci retracements, support/resistance) to validate wave counts, as momentum oscillators can be noisy in choppy markets.
Divergences: Watch for divergences (e.g., price makes a higher high, but ROC histogram bars are lower) to spot wave reversals, especially at Wave 3 or C ends.
Comparison to MACD: The ROC histogram is faster and more direct, making it ideal for short-term pulse waves, but it may be more volatile, so use with technical levels for precision.
Quantum Flow Navigator @DaviddTechQuantum Flow Navigator – DaviddTech
Precision Strategy Builder Powered by Adaptive Filters, Statistical Noise Reduction & Multi-Modal Confirmation
🚀 Bullish Signal : Enter when ALMA, FluxWave, and QuickSilver all confirm bullish trend, with high volume and valid noise filter state.
🔻 Bearish Signal : Enter short when all components align bearishly and filters validate the signal.
🚪 Exit : Automatically managed by dynamic SL/TP or indicator-based reversal logic.
✅ Overview & DaviddTech Methodology
Quantum Flow Navigator is an advanced, multi-component trading system engineered around the strict modular logic of the DaviddTech methodology .
It integrates every core component required for a fully rule-based and signal-driven strategy—baseline, confirmations, volume filter, exit system, and noise filter.
Designed for traders who demand structure, clarity, and data-backed decision-making on 15M, 1H, and 4H charts.
🔍 Indicator Components
Baseline: Adaptive ALMA Filter
Smooth and responsive dynamic trend detection, with momentum validation and optional filled zones for enhanced visual feedback.
Confirmation #1: FluxWave Oscillator
Developed from an enhanced Trendlio concept by @dudeowns , FluxWave uses ALMA-smoothed rate-of-change logic with configurable signal behavior.
Confirmation #2: QuickSilver Band System
Custom breakout engine that maps volatility envelopes using multi-layered deviation bands for clear confirmation of structure breaks and trend direction.
Volume Filter: Normalized Volume Energy
Innovative volume filter inspired by @ceyhun 's work. Filters trades by classifying energy into High, Normal, or Low based on normalized volume context.
Exit System: Dynamic Momentum Stop Loss
Choose from Smart Adaptive, Trailing, Stepped, Percentage, ATR, or Volatility-adjusted logic. Supports TP via risk/reward, ATR multiples, or percentage targets.
Noise Filtration: Quantum Statistical Noise Reduction
Fuses Kalman smoothing with wavelet decomposition to eliminate non-signal noise and improve trade quality and confidence.
🎨 Visual System & Dashboard
🚀/🔻/🚪 Emoji Labels : Buy, sell, and exit trades clearly marked for instant recognition.
Color-Shifting Bars : Reflect FluxWave’s trend bias in real-time.
ALMA Fill Zone : Visual trend envelope between price and ALMA baseline.
QuickSilver Bands : Volatility envelopes with graduated depth for support/resistance awareness.
SL & TP Visuals : Dynamic stop-loss and take-profit zones plotted directly on chart.
Navigator Panel : In-chart dashboard displays real-time trend status, volume energy, noise filter state, signal strength, and active position tracking.
📈 How to Trade with It
Entry Mode Selection : Choose between Combined, ALMA, FluxWave, QuickSilver, or Custom scoring logic.
Final Signals : Trigger only when confirmations align, volume energy is valid, and noise is low.
Dashboard Summary : Use real-time signal display to validate entry strength.
Timeframes : 15M–1H recommended for swing/intraday setups; 5M–15M for automation.
💡 Advanced Features
Entry Strength Scoring: Composite weight of all active components + filters.
Cooldown System: Limits excessive signals in volatile periods.
Multiple Exit Strategies: SL & TP modes with optional indicator-based exits.
Statistical Filtering: Wavelet + Kalman combination optimizes entry confidence.
Full Alert Suite: Covers entries, exits, filter triggers, volume states, and more.
🧠 Suggested Strategy Usage
Wait for full confirmation from ALMA, FluxWave, and QuickSilver.
Ensure volume energy is High and noise filter confirms trend clarity.
Use adaptive SL/TP or indicator-based exits.
Monitor dashboard for live signal strength ≥ threshold.
Use “Balanced” mode for general use; switch to “Aggressive” for tighter signals.
📝 Credits & Originality
Concept based on DaviddTech’s component-driven methodology .
FluxWave Oscillator built as an evolved version of Trendlio with full signal customization — credit @dudeowns .
Volume Energy Filter adapted from the work of @ceyhun .
Noise filtration and system architecture developed independently using Pine Script v6.
All code and logic is original, non-rehashed, and completely refactored to ensure uniqueness.
Quantum Flow Navigator fuses adaptive baselines, confirmation logic, energy-based filters, and statistical refinement into a precision signal engine—optimized for traders who value structure, clarity, and control.
Dragon Harmonic Pattern [TradingFinder] Dragon Detector🔵 Introduction
The Dragon Harmonic Pattern is one of the technical analysis tools that assists traders in identifying Potential Reversal Zones (PRZ). Resembling an "M" or "W" shape, this pattern is recognized in financial markets as a method for predicting bullish and bearish trends. By leveraging precise Fibonacci ratios and measuring price movements, traders can use this pattern to forecast market trends with high accuracy.
The Dragon Harmonic Pattern is built on the XABCD structure, where each point plays a significant role in shaping and forecasting price movements. Point X marks the beginning of the trend, representing the initial price movement. Point A indicates the first retracement, usually falling within the 0.380 to 0.620 range of the XA wave.
Next, point B signals the second retracement, which lies within 0.200 to 0.400 of the AB wave. Point C, acting as the hump of the pattern, is generally located within 0.800 to 1.100 of the XA wave. Finally, point D represents the endpoint of the pattern and the Potential Reversal Zone (PRZ), where the primary price reversal occurs.
In bullish scenarios, the Dragon Pattern indicates a reversal from a downtrend to an uptrend, where prices move upward from point D. Conversely, in bearish scenarios, prices decline after reaching point D. Accurate identification of this pattern through Fibonacci ratio analysis and PRZ examination can significantly increase the success rate of trades, enabling traders to adjust their strategies based on key market levels such as 0.618 or 1.100.
Due to its high accuracy in identifying Potential Reversal Zones (PRZ) and its alignment with Fibonacci ratios, the Dragon Harmonic Pattern is considered one of the most popular tools in technical analysis. Traders can use this pattern to pinpoint entry and exit points with greater confidence while minimizing trading risks.
Bullish :
Bearish :
🔵 How to Use
The Dragon Harmonic Pattern indicator helps traders identify bullish and bearish patterns in the market, allowing them to capitalize on available trading opportunities. By analyzing Fibonacci ratios and the XABCD structure, the indicator highlights Potential Reversal Zones (PRZ).
🟣 Bullish Dragon Pattern
In the Bullish Dragon Pattern, the price transitions from a downtrend to an uptrend after reaching point D. At this stage, points X, A, B, C, and D must be carefully identified.
Fibonacci ratios for these points are as follows: Point A should fall within 0.380 to 0.620 of the XA wave, point B within 0.200 to 0.400 of the AB wave, and point C within 0.800 to 1.100 of the XA wave.
When the price reaches point D, traders should look for bullish signals such as reversal candlesticks or increased trading volume to enter a buy position. The take-profit level can be set near the previous price high or based on the 1.272 Fibonacci ratio of the XA wave, while the stop-loss should be placed slightly below point D.
🟣 Bearish Dragon Pattern
In the Bearish Dragon Pattern, the price shifts from an uptrend to a downtrend after reaching point D. In this pattern, points X, A, B, C, and D must also be identified. Fibonacci ratios for these points are as follows: Point A should fall within 0.380 to 0.620 of the XA wave, point B within 0.200 to 0.400 of the AB wave, and point C within 0.800 to 1.100 of the XA wave.
Upon reaching point D, bearish signals such as reversal candlesticks or decreasing trading volume indicate the opportunity to enter a sell position. The take-profit level can be set near the previous price low or based on the 1.272 Fibonacci ratio of the XA wave, while the stop-loss should be placed slightly above point D.
By combining the Dragon Harmonic Pattern indicator with precise Fibonacci ratio analysis, traders can identify key opportunities while minimizing risks and improving their decision-making in both bullish and bearish market conditions.
🔵 Setting
🟣 Logical Setting
ZigZag Pivot Period : You can adjust the period so that the harmonic patterns are adjusted according to the pivot period you want. This factor is the most important parameter in pattern recognition.
Show Valid Forma t: If this parameter is on "On" mode, only patterns will be displayed that they have exact format and no noise can be seen in them. If "Off" is, the patterns displayed that maybe are noisy and do not exactly correspond to the original pattern.
Show Formation Last Pivot Confirm : if Turned on, you can see this ability of patterns when their last pivot is formed. If this feature is off, it will see the patterns as soon as they are formed. The advantage of this option being clear is less formation of fielded patterns, and it is accompanied by the latest pattern seeing and a sharp reduction in reward to risk.
Period of Formation Last Pivot : Using this parameter you can determine that the last pivot is based on Pivot period.
🟣 Genaral Setting
Show : Enter "On" to display the template and "Off" to not display the template.
Color : Enter the desired color to draw the pattern in this parameter.
LineWidth : You can enter the number 1 or numbers higher than one to adjust the thickness of the drawing lines. This number must be an integer and increases with increasing thickness.
LabelSize : You can adjust the size of the labels by using the "size.auto", "size.tiny", "size.smal", "size.normal", "size.large" or "size.huge" entries.
🟣 Alert Setting
Alert : On / Off
Message Frequency : This string parameter defines the announcement frequency. Choices include: "All" (activates the alert every time the function is called), "Once Per Bar" (activates the alert only on the first call within the bar), and "Once Per Bar Close" (the alert is activated only by a call at the last script execution of the real-time bar upon closing). The default setting is "Once per Bar".
Show Alert Time by Time Zone : The date, hour, and minute you receive in alert messages can be based on any time zone you choose. For example, if you want New York time, you should enter "UTC-4". This input is set to the time zone "UTC" by default.
🔵 Conclusion
The Dragon Harmonic Pattern is an advanced and practical technical analysis tool that aids traders in accurately predicting bullish and bearish trends by identifying Potential Reversal Zones (PRZ) and utilizing Fibonacci ratios. Built on the XABCD structure, this pattern stands out for its flexibility and precision in identifying price movements, making it a valuable resource among technical analysts. One of its key advantages is its compatibility with other technical tools such as trendlines, support and resistance levels, and Fibonacci retracements.
By using the Dragon Harmonic Pattern indicator, traders can accurately determine entry and exit points for their trades. The indicator analyzes key Fibonacci ratios—0.380 to 0.620, 0.200 to 0.400, and 0.800 to 1.100—to identify critical levels such as price highs and lows, offering precise trading strategies. In bullish scenarios, traders can profit from rising prices, while in bearish scenarios, they can capitalize on price declines.
In conclusion, the Dragon Harmonic Pattern is a highly reliable tool for identifying trading opportunities with exceptional accuracy. However, for optimal results, it is recommended to combine this pattern with other analytical tools and thoroughly assess market conditions. By utilizing this indicator, traders can reduce their trading risks while achieving higher profitability and confidence in their trading strategies.
Next Candle Predictor with Auto HedgingThe "Next Candle Predictor with Auto Hedging" is a Pine Script indicator designed for use on TradingView. It combines predictive analysis and basic hedging techniques to assist traders in making informed decisions. Here's a detailed explanation suitable for public sharing on TradingView:
Overview
This script predicts the closing price of the next candle based on the current candle's open and close prices. It also includes an auto hedging feature that suggests potential hedging levels to mitigate risk based on the predicted price movement. The indicator is particularly useful for traders looking to enhance their trading strategies with predictive analytics.
Key Features
Next Candle Prediction:
The indicator analyzes the current candle's data (open and close prices) to predict whether the next candle will close higher or lower.
If the current candle is bullish (close > open), it predicts a higher close for the next candle. Conversely, if the candle is bearish, it predicts a lower close.
Auto Hedging:
The script calculates a hedging level based on the predicted close price.
If the predicted close indicates a bullish move, the hedge level is set slightly below the predicted close, suggesting where a trader might consider placing a hedge. If the prediction indicates a bearish move, the hedge level is set above the predicted close.
Elliott Wave Analysis:
The script includes a basic implementation of identifying significant price movements, akin to Elliott Wave analysis, by detecting peaks and troughs over a specified number of bars (wave length).
This can help traders identify potential trend reversals or continuations.
How It Works
Input Parameters: Users can customize the waveLength parameter, which determines how many bars back the script looks to identify significant highs and lows.
Peak and Trough Detection: The script identifies the highest high and lowest low within the specified wave length, plotting these points on the chart for visual reference.
Prediction Logic: The predicted close is calculated based on the current candle's behavior, allowing traders to anticipate price movements.
Hedging Level Calculation: The script dynamically calculates a hedging level based on the predicted close, providing a visual cue for potential risk management strategies.
Visual Representation
The indicator plots:
Elliott Wave Highs: Marked in green.
Elliott Wave Lows: Marked in red.
Predicted Close: Shown as a blue step line.
Hedge Level: Displayed as an orange step line.
Benefits
Enhanced Decision-Making: By providing predictions and potential hedging levels, traders can make more informed decisions about entering or exiting positions.
Risk Management: The auto hedging feature helps traders manage risk by suggesting levels where they might place hedges against adverse price movements.
Customizable: The script allows for user-defined parameters, making it adaptable to different trading strategies and market conditions.
Conclusion
The "Next Candle Predictor with Auto Hedging" indicator is a powerful tool for traders seeking to enhance their trading strategies with predictive analytics and risk management techniques. By utilizing this indicator, traders can gain insights into potential price movements and make more informed trading decisions.
Feel free to explore the script, customize it to fit your trading style, and engage with the TradingView community for further insights and improvements!
Related
Trend Direction Sequence | Auto-Multi-TimeframeThe main benefit of this indicator is the ability to see multiple higher timeframes at ones to get a better overview of signals that could mark possible trend reversals with more weight than those on the selected timeframe. Since the higher timeframes are calculated automatically, the user needs to set a Period Multiplier that multiplies the selected timeframe several times to determine the higher timeframes. Equal periods are filtered out. And the current highest timeframe is capped at 1 year by TradingView.
It is possible to alter the sequence Count Limit and the underlying Wavelength. The Wavelength defines the distance between the starting and ending candle. This builds the minimum condition to find a trend. A longer Wavelength means that the distortions between the start and end candle can be bigger, so it can become easier to find a trending sequence. But be careful not to set the length too high as this could mean that the resulting sequence does not really represent a trend anymore. The Count Limit defines the completion of a trending sequence. A higher number makes it more difficult to find a completed sequence, but also makes the result more reliable. If the Wavelength is changed, the Count Limit should be adjusted accordingly.
There is also a qualifier for the completion of a sequence. A completed sequence only will be labeled on the chart, if it is proved that the lowest low/highest high of the last two candlesticks of a period is lower/higher than that of the previous two candlesticks. It does not require the trend to be continuous on the last candlestick. On the contrary, a trend shift may already have begun.
By default, the labeling of completed sequences will appear on the highs and lows of the specific periods. Because the higher periods will take time and several candlesticks to appear, the labels will be redrawn accordingly. As an option it is possible to disable the Count Limit for completed sequences so that the labels will be fluently redrawn until the corresponding sequences are interrupted by trend breaks. Only activate this option, if it can serve a plausible strategy.
The count status of all sequences in the specific timeframe periods is listed in a table. Also the results of the trends in higher timeframes are accumulated and combined into an overall trend. Positive trends are counted as positive, negative in the opposite case. To see the resulting Trend Shift Signals, the user can set a filter under 100% so that not all of them will be filtered out and therefore labeled on the chart (this signals cannot be redrawn). An “External Indicator Analysis Overlay” can be used to analyze the profitability with the provided Trend Shift Signal (TSS) which switches from 0 to 1, if the trend becomes positive or from 0 to -1, if the trend becomes negative.
Time Wolna_2021_iun3[wozdux] Description of the Time_Wolna indicator
The indicator is designed to study the behavior of time. There are many indicators that study just the price, a little less indicators that study the volume of trading and vanishingly few indicators that study time.
This is not an oscillator, it does not have oversold or overbought levels. This indicator has an indefinite beginning and an indefinite end. Its value is not in the absolute values of the indicator, but in relative ones. This indicator calculates the time of price rise and the time of price decline. It clearly shows how long the price rises and how long the price falls.
The initial idea was to use my RSIVol indicator to study the time. Each bar is counted as a unit of time. If the price rises during the period of one bar, then one is added, if the price falls, then one is subtracted. By default, the blue line shows this time movement according to the RsiVol indicator.
The basic RsiVol indicator is shown at the bottom of the diagram. The bill goes along the blue line, which calculates the movement of the volume price. If the blue RSIVol line is above the yellow level, then the blue Time_Wolna time line is colored green. If the blue line in the base RsiVol indicator falls below the lower yellow level, then the blue time line of the Time_Wolna indicator turns red.
The result is a broken line that clearly shows the waves of rising and falling prices. In principle, the time indicator makes it easier to recognize waves.
It is known that time plays an important role in Elliott wave analysis, although in practice this is almost never done. The mention of Elliott is just a lyrical digression.
Time is very difficult to study. This indicator does not give clear buy or sell signals. This is just an analysis tool to help analysts.
In addition to the RsiVol indicator, simply the Rsi from the price and a simple moving average from the price are also used.
So, the settings of this indicator.
"switch Price == close <==> ( High+Low)/2" -- select the base price in all subsequent calculations
"Key EMA=> True=ema(Price); False=ema(Price*Volume)" --The key for switching the moving average from the price or from the volume price.
"T==> EMA(price, T)" --The period for calculating the moving average
" key red==> Yes/No Rsi")--the key turns on or off the RSI line red line
"key green==> Yes/No Orsi") --the key turns on or off the Volume RSI line green line
" key olive==> Yes/No RsiVol200 " -- the key enables or disables the Volumetric RSIVol200 olive line. This is RsiVol minus the 200-period moving average.
"keyVol blue==> Yes/No " - the key enables or disables the base blue line RSIVol
"keyVol blue==> V->tt(RsiVol) ->tt(ema(Price))"—The blue line selection will be calculated as the time from RSIVol or as the time from the moving average EMA.
"keyVol blue==> : 1=Time, 2=Time* price, 3=Time*(Ci-Ck) 4=Time*Volume, 5=Time*price*Volume")- selection for the blue baseline. By default, the time of the price rise or fall is calculated simply. Key=1. But you can investigate the joint influence of time and price and then the key is=2. If we study the combined effect of time and price changes per bar, then the key=3. If we study the joint influence of time and volume, then the key=4. If we study the joint influence of time, price and volume, then the key=5.
"key RsiO red + green==> : 1=Time, 2=Time*Price, 3=Time*(Ci-Ck) 4=Time*Volume, 5=Time*Price*Volume") - - - similar settings for the red green line. By default, the time of the price rise or fall is calculated simply. Key=1. But you can investigate the joint influence of time and price and then the key is=2. If we study the combined effect of time and price changes per bar, then the key=3. If we study the joint influence of time and volume, then the key=4. If we study the joint influence of time, price and volume, then the key=5.
"Key Color – - here you can disable changing the color of the blue line to green or red when the base indicator RsiVol exits above the upper and below the lower levels.
"Level nul ==> * Down Level Rsi - screen configuration in order to raise or lower chart
"Level nul ==> * Down Level ORsi -- beauty setup in order to raise or lower chart
"Level nul ==> * DownLevel RsiVol200 -- beauty setup in order to raise or lower chart
"blue =volume * price" – period for calculation of volumetric rates
"blue => RSIVOL(Volume*price,len) and EMA" – the period for calculating RsiVol
"blue__o1=> ema ( RSIVOL, o1)" – additional smoothing RsiVol
"red=rsi (Price,14)" – the period for calculating Rsi
"red= ema ( RSI ,3)" -- additional smoothing Rsi
"fuchsia__ => RsiVol200 (vp,200)" - the period for calculating RsiVol200
"fuchsia__o2=> ema ( RSIVOL200 , o2)" -- additional smoothing RsiVol200
To study the time between two fixed dates. Setting the start point of the calculation and the end point of the calculation
"Data(0)=Year" – the year of the start date
"Data(0)= Month" – the month of the start date
"Data (0)=Day" the day of the start date
"Data(1)=Year" – the year of the end date.
"Data(1)=Year" – month of the end date.
"Data(1)=Day" -- the day of the end date.
--------русский вариант описания ------
Описание индикатора Time_Wolna
Индикатор призван изучать поведение времени. Есть много индикаторов изучающих просто цену, немного меньше индикаторов изучающих объем торгов и исчезающе мало индикаторов, изучающих время.
Это не осциллятор у него нет уровней перепроданности или перекупленности. Данный индикатор имеет неопределенное начало и неопределенный конец. Ценность его не в абсолютных значениях индикатора, а в относительных. Этот индикатор высчитывает время подъема цены и время снижения цены. Он наглядно показывает сколько времени цена поднимается и сколько времени цена опускается.
Первоначальная идея была использовать мой индикатор RSIVol для изучения времени. Каждый бар считается за единицу времени. Если цена поднимается за период одного бара, то прибавляется единица, если цена опускается, то вычитается единица. По умолчанию голубая линия показывает такое движения времени по индикатору RsiVol.
Внизу на диаграмме показан базовый индикатор RsiVol. Счёт идет по синей линии, которая вычисляет движение объемной цены. Если синяя линия RSIVol находится выше желтого уровня, то голубая линия времени Time_Wolna окрашивается в зеленый цвет. Если синяя линия в базовом индикаторе RsiVol опускается ниже нижнего желтого уровня, то голубая линия времени индикатора Time_Wolna окрашивается в красный цвет.
В результате получается ломанная линия, четко показывающая волны восхождения и снижения цены. В принципе индикатор времени позволяет легче распознавать волны.
Известно, что время играет важную роль в волновом анализе Эллиотта, хотя на практике это почти никогда не делается. Упоминание Эллиотта это просто лирическое отступление.
Время очень трудно изучать. Этот индикатор не дает четких сигналов на покупку или продажу. Это всего лишь инструмент анализа в помощь аналитикам.
Кроме индикатора RsiVol, используются и просто Rsi от цены и простая скользящая средняя от цены.
Итак, настройки данного индикатора.
"switch Price == close <==> ( High+Low)/2" -- выбираем базовую цену во всех последующих вычислениях
"Key EMA=> True=ema(Price); False=ema(Price*Volume)" --Ключ переключения скользящей средней от цены или от объемной цены.
" T==> EMA(price,T)"--Период вычисления скользящей средней
"key red==> Yes/No Rsi")--ключ включает или выключает линию RSI красная линия
"key green==> Yes/No Orsi") --ключ включает или выключает линию Объемной RSI зеленая линия
"key olive==> Yes/No RsiVol200" -- ключ включает или выключает линию Объемной RSIVol200 оливковая линия. Это RsiVol минус 200-периодная скользящая средняя.
"keyVol blue==> Yes/No " – ключ включает или выключает базовую голубую линию RSIVol
"keyVol blue==> V->tt(RsiVol) ->tt(ema(Price))"—выбор голубая линия будет вычисляться как время от RSIVol или как время от скользящей средней EMA.
"keyVol blue==> : 1=Time, 2=Time* price, 3=Time*(Ci-Ck) 4=Time*Volume, 5=Time*price*Volume")—выбор для голубой базовой линии. По умолчанию вычисляется просто время подъема или опускания цены. Ключ=1. Но можно исследовать совместное влияние времени и цены и тогда ключ=2. Если изучаем совместное влияние времени и изменения цены за один бар, то ключ=3. Если изучаем совместное влияние времени и объема, то ключ=4. Если изучаем совместное влияние времени, цены и объема, то ключ=5.
"key RsiO red + green==> : 1=Time, 2=Time*Price, 3=Time*(Ci-Ck) 4=Time*Volume, 5=Time*Price*Volume") ---аналогичные настройки для красной зеленой линии. По умолчанию вычисляется просто время подъема или опускания цены. Ключ=1. Но можно исследовать совместное влияние времени и цены и тогда ключ=2. Если изучаем совместное влияние времени и изменения цены за один бар, то ключ=3. Если изучаем совместное влияние времени и объема, то ключ=4. Если изучаем совместное влияние времени, цены и объема, то ключ=5.
"Key Color" – здесь можно отключить изменение цвета голубой линии на зеленый или красный в моменты выхода базового индикатора RsiVol выше верхнего и ниже нижнего уровней.
"Level nul ==> * Down Level Rsi - косметическая настройка для того, чтобы поднять или опустить график
"Level nul ==> * Down Level ORsi -- косметическая настройка для того, чтобы поднять или опустить график
"Level nul ==> * DownLevel RsiVol200 -- косметическая настройка для того, чтобы поднять или опустить график
" blue =>volume * price" – период для вычисления объемной цены
" blue => RSIVOL(Volume*price,len) and EMA" – период для вычисления RsiVol
"blue__o1=> ema ( RSIVOL, o1)" – дополнительное сглаживание RsiVol
" red=rsi (Price,14)" – период для вычисления Rsi
" red= ema ( RSI ,3)" -- дополнительное сглаживание Rsi
"fuchsia__ => RsiVol200 (vp,200)" -- период для вычисления RsiVol200
"fuchsia__o2=> ema ( RSIVOL200 , o2)" -- дополнительное сглаживание RsiVol200
Для исследования времени между двумя фиксированными датами. Задаем начальную точку вычисления и конечную точку вычисления
"Data(0)=Year" – год начальной даты
"Data(0)= Month" – месяц начальной даты
"Data(0)=Day" день начальной даты
"Data(1)=Year" – год конечной даты.
"Data(1)=Year" – месяц конечной даты.
"Data(1)=Day" -- день конечной даты.
Amazing Oscillator MTF MulticolorIngles
The amazing multitemporal oscillator, allows you to see in a single graph the Waves that move the market in different temporalities, that is, you will be able to see the market trend, the impulse movement, the forced movement, and the entry and exit points, as well as also how both collide with each other, to understand why the smaller waves succumb to the impulse of the larger waves.
Elliot already described them as such, in his legacy of the Elliot waves and their different sub-waves, just as Wycoff spoke of the theory of effort and result.
Español:
El oscilador asombroso multitemporal, permite ver en una sola grafica las Ondas que mueven el mercado en diferentes temporalidades, es decir, podrás ver la tendencia del mercado, el movimiento de impulso, el movimiento de fuerza y los puntos de entrada y salida, así como también como ambos chocan entre si, para entender porque las ondas mas pequeñas sucumben al impulso de las ondas de mayor tamaño.
Ya Elliot las describía como tal, en su legado de las ondas de Elliot y sus diferentes sub-ondas, al igual que Wycoff hablaba de la teoría de esfuerzo y resultado.
Amazing Oscillator MTF plusIngles
The amazing multitemporal oscillator, allows you to see in a single graph the Waves that move the market in different temporalities, that is, you will be able to see the market trend, the impulse movement, the force movement and the entry and exit points, as well as also how both collide with each other, to understand why the smaller waves succumb to the impulse of the larger waves.
Elliot already described them as such, in his legacy of the Elliot waves and their different sub-waves, just as Wycoff spoke of the theory of effort and result.
Español:
El oscilador asombroso multitemporal, permite ver en una sola grafica las Ondas que mueven el mercado en diferentes temporalidades, es decir, podrás ver la tendencia del mercado, el movimiento de impulso, el movimiento de fuerza y los puntos de entrada y salida, así como también como ambos chocan entre si, para entender porque las ondas mas pequeñas sucumben al impulso de las ondas de mayor tamaño.
Ya Elliot las describía como tal, en su legado de las ondas de Elliot y sus diferentes sub-ondas, al igual que Wycoff hablaba de la teoría de esfuerzo y resultado.
MJ ECT== One Line Introduction ==
ECT is a multi-level, trend focused technical indicator based on a three-step hierarchical approach - comprising the tide, wave, and ripple - to trend identification.
== Indicator Philosophy ==
The author believes that market trends can be understood in a three-step hierarchy, with tide at the top, wave in the middle, and ripple at the bottom, corresponding to long-, middle-, and short-term momentum in the stock price. This indicator therefore comprises three technical indicators which aims to reflect the abovementioned features of a trend. These three components are True Strength Index (TSI), Exponential Moving Averages ( EMA ), and Commodity Channel Index ( CCI ).
== Indicator Components and Breakdown ==
True Strength Index (TSI) -> Tide
A 20-period TSI is used to visualize the bullish or bearish sentiment surrounding the stock. Crossovers above the zero line are interpreted as bullish while crossovers below the zero line are interpreted as bearish . This is painted into the background where green represents bullish and red represents bearish . While the background is red ( bearish ), no bullish positions should be taken. Hence, the TSI painted background acts as a directional bias filter and going against the bias is not recommended. After understanding the directional bias, the user can delve further into the areas of value for the stock in the Wave.
Exponential Moving Averages ( EMA ) -> Wave
Four EMA are used (20, 50, 100, 200) to identify the dynamic support and resistance waves in a trending market. Stock price pullbacks into any of these EMA represent areas of value where the user can consider taking positions. The correct EMA to use depends on individual stock's behavior, with multiple bounces on a specified EMA being the priority. After understanding which wave best reflects the area of value of a stock, the user can move on to the Ripple to time their entries.
Commodity Channel Index ( CCI ) -> Ripple
A 5-period CCI is used to identify short-term oversold conditions where prices are on discount. Discount is defined by the 5-period CCI crossing below -100 as it reflects a weekly oversold condition. The indicator will display a small triangle below the candle when this condition is met.
== Ready To Deploy Field Manual ==
When background is painted red, do nothing.
When background is painted green, begin thinking of bullish opportunities.
Look for the specific EMA that has the most bounces of stock price in recent months, this is the area of value to look for buying opportunity.
For the candles that intersect the EMA you identified above, watch for the appearance of a small triangle below the candle that tells you the entry timing.
When the entry timing signal triangle appears, remember the High of that candle and buy your position when the subsequent candle breaks above this High.
If the High is not broken above in the next immediate candle, remember the newer High of the newer candle (basically follow / trail the latest High until a break above is hit).
If the background turns from green to red, stop following the High and do not enter because the market sentiment has changed to bearish .
If you are holding an existing position and the background turns red, consider exiting the position. You may consider remembering the Low of the candle and exit your position if this Low is broken below on a subsequent candle.
== Best Wishes ==
The author wishes the best success for all users of this technical indicator.
[blackcat] L2 Ehlers Autocorrelation IndicatorLevel: 2
Background
John F. Ehlers introduced Autocorrelation Indicator in his "Cycle Analytics for Traders" chapter 8 on 2013.
Function
If we correlate a waveform composed of perfectly random numbers by itself, the correlation will be perfect. However, if we lag one of the data streams by just one bar, the correlation will be dramatically reduced. In a long memory process with normally distributed random numbers the autocorrelation follows the power law.
One of the underlying principles of technical analysis is that market data do not follow this power law of an efficient market, and we therefore can extract information from the partial correlation of the autocorrelation function. For example, assume the data being examined is a perfect sine wave whose period is 20 bars. The autocorrelation with zero lag, averaged over one full period of the sine wave, is unity. That is, the correlation is perfect. Introducing a lag of one bar in the autocorrelation process causes the average correlation to be decreased slightly. Introducing another bar of lag further decreases the average correlation, and so on. That is, until a lag of 10 bars is reached. In this case, the positive alternation of the sine wave is correlated with the negative alternation of the lagged waveform and the negative alternation of the sine wave is correlated with the positive alternation of the lagged waveform, with the result that perfect anticorrelation has been reached. Continued lag increases causes the average correlation to increase until a lag of 20 bars is reached. When the lag is equal to the period of the sine wave waveform, the correlation is again perfect. In this theoretical example, the correlation values as a function of lag vary exactly as a sine wave.
Market data are considerably messier than purely random numbers or perfect sine waves but contain features of both. However, the characteristics that are uncovered by autocorrelation offer unique trading perspectives. Aside from appearing psychedelic, there are two distinct characteristics of the autocorrelation indicator using minimum averaging. First, there is a sharp reversal from red to yellow and from yellow to red at the timing of price reversals for all periods of lag. Second, there is a variation of the thickness of the bars and the number of bars over the vertical range of the indicator as a function of time.
Key Signal
Corr --> Pearson correlation data array
Pros and Cons
I am sorry this script is NOT 100% as original Ehlers works but I modified it accordingly which demostrated with better visual effect.
Remarks
The 47th script for Blackcat1402 John F. Ehlers Week publication.
Courtesy of @RicardoSantos for RGB functions.
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.
Vegas tunnelHi all,
This is the first step in putting together a more comprehensive suite of indicators and strategies based around the original Vegas tunnel method.
You will need to know what that is before trying to use this indicator. I would implore you to take the time to read the document. It's free to the universe and is a very valuable piece of work in my opinion.
Here is the link to the original documentation dl.fxf1.com
This indicator is set up to use the original levels as described by Vegas. Future releases will allow for more custom levels.
A note on the target waves. Vegas gives us the levels of 55, 89 and 233...all in FX pips. You will need to adjust that for your instrument and it is your personal preference. If you are using BTC , you might use $55, $89 etc, for ETH $5.50, $8.90 etc, for S+P 55, 89, 233 or for FX, the number might be 0.0055 etc
The indicator has been left blank so you can fill the target waves in yourself.
A note on the templates
The original template is simply as Vegas described it in his document, change it as you wish
The TD template comes from where I first was introduced to the concept. I can't mention the full source here, but some of you will know to what I am referring to. A massive thanks to TD for all the material they have provided the world.
The HH (Hero Hedge) template is just my way of looking at the wave. It's green when the faster MA is above the slower MA and red for the opposite. It doesn't really mean much, it's just a visual reference. Perhaps you can use it to filter signals if you so wish.
Finally, some of you may notice that I am an amateur coder at best. If you think you can improve or tidy up the code, then by all means, please reach out and collaborate with me.
I am trying to produce something to the benefit of all. I hope this can help you. If it does, then please pay it forward as I am trying to do.
Hero Hedge.
Vegas tunnelHi all,
This is the first step in putting together a more comprehensive suite of indicators and strategies based around the original Vegas tunnel method.
You will need to know what that is before trying to use this indicator. I would implore you to take the time to read the document. It's free to the universe and is a very valuable piece of work in my opinion.
Here is the link to the original documentation dl.fxf1.com
This indicator is set up to use the original levels as described by Vegas. Future releases will allow for more custom levels.
A note on the target waves. Vegas gives us the levels of 55, 89 and 233...all in FX pips. You will need to adjust that for your instrument and it is your personal preference. If you are using BTC , you might use $55, $89 etc, for ETH $5.50, $8.90 etc, for S+P 55, 89, 233 or for FX, the number might be 0.0055 etc
The indicator has been left blank so you can fill the target waves in yourself.
A note on the templates
The original template is simply as Vegas described it in his document, change it as you wish
The TD template comes from where I first was introduced to the concept. I can't mention the full source here, but some of you will know to what I am referring to. A massive thanks to TD for all the material they have provided the world.
The HH (Hero Hedge) template is just my way of looking at the wave. It's green when the faster MA is above the slower MA and red for the opposite. It doesn't really mean much, it's just a visual reference. Perhaps you can use it to filter signals if you so wish.
Finally, some of you may notice that I am an amateur coder at best. If you think you can improve or tidy up the code, then by all means, please reach out and collaborate with me.
I am trying to produce something to the benefit of all. I hope this can help you. If it does, then please pay it forward as I am trying to do.
Hero Hedge.
Grothendieck-Teichmüller Geometric SynthesisDskyz's Grothendieck-Teichmüller Geometric Synthesis (GTGS)
THEORETICAL FOUNDATION: A SYMPHONY OF GEOMETRIES
The 🎓 GTGS is built upon a revolutionary premise: that market dynamics can be modeled as geometric and topological structures. While not a literal academic implementation—such a task would demand computational power far beyond current trading platforms—it leverages core ideas from advanced mathematical theories as powerful analogies and frameworks for its algorithms. Each component translates an abstract concept into a practical market calculation, distinguishing GTGS by identifying deeper structural patterns rather than relying on standard statistical measures.
1. Grothendieck-Teichmüller Theory: Deforming Market Structure
The Theory : Studies symmetries and deformations of geometric objects, focusing on the "absolute" structure of mathematical spaces.
Indicator Analogy : The calculate_grothendieck_field function models price action as a "deformation" from its immediate state. Using the nth root of price ratios (math.pow(price_ratio, 1.0/prime)), it measures market "shape" stretching or compression, revealing underlying tensions and potential shifts.
2. Topos Theory & Sheaf Cohomology: From Local to Global Patterns
The Theory : A framework for assembling local properties into a global picture, with cohomology measuring "obstructions" to consistency.
Indicator Analogy : The calculate_topos_coherence function uses sine waves (math.sin) to represent local price "sections." Summing these yields a "cohomology" value, quantifying price action consistency. High values indicate coherent trends; low values signal conflict and uncertainty.
3. Tropical Geometry: Simplifying Complexity
The Theory : Transforms complex multiplicative problems into simpler, additive, piecewise-linear ones using min(a, b) for addition and a + b for multiplication.
Indicator Analogy : The calculate_tropical_metric function applies tropical_add(a, b) => math.min(a, b) to identify the "lowest energy" state among recent price points, pinpointing critical support levels non-linearly.
4. Motivic Cohomology & Non-Commutative Geometry
The Theory : Studies deep arithmetic and quantum-like properties of geometric spaces.
Indicator Analogy : The motivic_rank and spectral_triple functions compute weighted sums of historical prices to capture market "arithmetic complexity" and "spectral signature." Higher values reflect structured, harmonic price movements.
5. Perfectoid Spaces & Homotopy Type Theory
The Theory : Abstract fields dealing with p-adic numbers and logical foundations of mathematics.
Indicator Analogy : The perfectoid_conv and type_coherence functions analyze price convergence and path identity, assessing the "fractal dust" of price differences and price path cohesion, adding fractal and logical analysis.
The Combination is Key : No single theory dominates. GTGS ’s Unified Field synthesizes all seven perspectives into a comprehensive score, ensuring signals reflect deep structural alignment across mathematical domains.
🎛️ INPUTS: CONFIGURING THE GEOMETRIC ENGINE
The GTGS offers a suite of customizable inputs, allowing traders to tailor its behavior to specific timeframes, market sectors, and trading styles. Below is a detailed breakdown of key input groups, their functionality, and optimization strategies, leveraging provided tooltips for precision.
Grothendieck-Teichmüller Theory Inputs
🧬 Deformation Depth (Absolute Galois) :
What It Is : Controls the depth of Galois group deformations analyzed in market structure.
How It Works : Measures price action deformations under automorphisms of the absolute Galois group, capturing market symmetries.
Optimization :
Higher Values (15-20) : Captures deeper symmetries, ideal for major trends in swing trading (4H-1D).
Lower Values (3-8) : Responsive to local deformations, suited for scalping (1-5min).
Timeframes :
Scalping (1-5min) : 3-6 for quick local shifts.
Day Trading (15min-1H) : 8-12 for balanced analysis.
Swing Trading (4H-1D) : 12-20 for deep structural trends.
Sectors :
Stocks : Use 8-12 for stable trends.
Crypto : 3-8 for volatile, short-term moves.
Forex : 12-15 for smooth, cyclical patterns.
Pro Tip : Increase in trending markets to filter noise; decrease in choppy markets for sensitivity.
🗼 Teichmüller Tower Height :
What It Is : Determines the height of the Teichmüller modular tower for hierarchical pattern detection.
How It Works : Builds modular levels to identify nested market patterns.
Optimization :
Higher Values (6-8) : Detects complex fractals, ideal for swing trading.
Lower Values (2-4) : Focuses on primary patterns, faster for scalping.
Timeframes :
Scalping : 2-3 for speed.
Day Trading : 4-5 for balanced patterns.
Swing Trading : 5-8 for deep fractals.
Sectors :
Indices : 5-8 for robust, long-term patterns.
Crypto : 2-4 for rapid shifts.
Commodities : 4-6 for cyclical trends.
Pro Tip : Higher towers reveal hidden fractals but may slow computation; adjust based on hardware.
🔢 Galois Prime Base :
What It Is : Sets the prime base for Galois field computations.
How It Works : Defines the field extension characteristic for market analysis.
Optimization :
Prime Characteristics :
2 : Binary markets (up/down).
3 : Ternary states (bull/bear/neutral).
5 : Pentagonal symmetry (Elliott waves).
7 : Heptagonal cycles (weekly patterns).
11,13,17,19 : Higher-order patterns.
Timeframes :
Scalping/Day Trading : 2 or 3 for simplicity.
Swing Trading : 5 or 7 for wave or cycle detection.
Sectors :
Forex : 5 for Elliott wave alignment.
Stocks : 7 for weekly cycle consistency.
Crypto : 3 for volatile state shifts.
Pro Tip : Use 7 for most markets; 5 for Elliott wave traders.
Topos Theory & Sheaf Cohomology Inputs
🏛️ Temporal Site Size :
What It Is : Defines the number of time points in the topological site.
How It Works : Sets the local neighborhood for sheaf computations, affecting cohomology smoothness.
Optimization :
Higher Values (30-50) : Smoother cohomology, better for trends in swing trading.
Lower Values (5-15) : Responsive, ideal for reversals in scalping.
Timeframes :
Scalping : 5-10 for quick responses.
Day Trading : 15-25 for balanced analysis.
Swing Trading : 25-50 for smooth trends.
Sectors :
Stocks : 25-35 for stable trends.
Crypto : 5-15 for volatility.
Forex : 20-30 for smooth cycles.
Pro Tip : Match site size to your average holding period in bars for optimal coherence.
📐 Sheaf Cohomology Degree :
What It Is : Sets the maximum degree of cohomology groups computed.
How It Works : Higher degrees capture complex topological obstructions.
Optimization :
Degree Meanings :
1 : Simple obstructions (basic support/resistance).
2 : Cohomological pairs (double tops/bottoms).
3 : Triple intersections (complex patterns).
4-5 : Higher-order structures (rare events).
Timeframes :
Scalping/Day Trading : 1-2 for simplicity.
Swing Trading : 3 for complex patterns.
Sectors :
Indices : 2-3 for robust patterns.
Crypto : 1-2 for rapid shifts.
Commodities : 3-4 for cyclical events.
Pro Tip : Degree 3 is optimal for most trading; higher degrees for research or rare event detection.
🌐 Grothendieck Topology :
What It Is : Chooses the Grothendieck topology for the site.
How It Works : Affects how local data integrates into global patterns.
Optimization :
Topology Characteristics :
Étale : Finest topology, captures local-global principles.
Nisnevich : A1-invariant, good for trends.
Zariski : Coarse but robust, filters noise.
Fpqc : Faithfully flat, highly sensitive.
Sectors :
Stocks : Zariski for stability.
Crypto : Étale for sensitivity.
Forex : Nisnevich for smooth trends.
Indices : Zariski for robustness.
Timeframes :
Scalping : Étale for precision.
Swing Trading : Nisnevich or Zariski for reliability.
Pro Tip : Start with Étale for precision; switch to Zariski in noisy markets.
Unified Field Configuration Inputs
⚛️ Field Coupling Constant :
What It Is : Sets the interaction strength between geometric components.
How It Works : Controls signal amplification in the unified field equation.
Optimization :
Higher Values (0.5-1.0) : Strong coupling, amplified signals for ranging markets.
Lower Values (0.001-0.1) : Subtle signals for trending markets.
Timeframes :
Scalping : 0.5-0.8 for quick, strong signals.
Swing Trading : 0.1-0.3 for trend confirmation.
Sectors :
Crypto : 0.5-1.0 for volatility.
Stocks : 0.1-0.3 for stability.
Forex : 0.3-0.5 for balance.
Pro Tip : Default 0.137 (fine structure constant) is a balanced starting point; adjust up in choppy markets.
📐 Geometric Weighting Scheme :
What It Is : Determines the framework for combining geometric components.
How It Works : Adjusts emphasis on different mathematical structures.
Optimization :
Scheme Characteristics :
Canonical : Equal weighting, balanced.
Derived : Emphasizes higher-order structures.
Motivic : Prioritizes arithmetic properties.
Spectral : Focuses on frequency domain.
Sectors :
Stocks : Canonical for balance.
Crypto : Spectral for volatility.
Forex : Derived for structured moves.
Indices : Motivic for arithmetic cycles.
Timeframes :
Day Trading : Canonical or Derived for flexibility.
Swing Trading : Motivic for long-term cycles.
Pro Tip : Start with Canonical; experiment with Spectral in volatile markets.
Dashboard and Visual Configuration Inputs
📋 Show Enhanced Dashboard, 📏 Size, 📍 Position :
What They Are : Control dashboard visibility, size, and placement.
How They Work : Display key metrics like Unified Field , Resonance , and Signal Quality .
Optimization :
Scalping : Small size, Bottom Right for minimal chart obstruction.
Swing Trading : Large size, Top Right for detailed analysis.
Sectors : Universal across markets; adjust size based on screen setup.
Pro Tip : Use Large for analysis, Small for live trading.
📐 Show Motivic Cohomology Bands, 🌊 Morphism Flow, 🔮 Future Projection, 🔷 Holographic Mesh, ⚛️ Spectral Flow :
What They Are : Toggle visual elements representing mathematical calculations.
How They Work : Provide intuitive representations of market dynamics.
Optimization :
Timeframes :
Scalping : Enable Morphism Flow and Spectral Flow for momentum.
Swing Trading : Enable all for comprehensive analysis.
Sectors :
Crypto : Emphasize Morphism Flow and Future Projection for volatility.
Stocks : Focus on Cohomology Bands for stable trends.
Pro Tip : Disable non-essential visuals in fast markets to reduce clutter.
🌫️ Field Transparency, 🔄 Web Recursion Depth, 🎨 Mesh Color Scheme :
What They Are : Adjust visual clarity, complexity, and color.
How They Work : Enhance interpretability of visual elements.
Optimization :
Transparency : 30-50 for balanced visibility; lower for analysis.
Recursion Depth : 6-8 for balanced detail; lower for older hardware.
Color Scheme :
Purple/Blue : Analytical focus.
Green/Orange : Trading momentum.
Pro Tip : Use Neon Purple for deep analysis; Neon Green for active trading.
⏱️ Minimum Bars Between Signals :
What It Is : Minimum number of bars required between consecutive signals.
How It Works : Prevents signal clustering by enforcing a cooldown period.
Optimization :
Higher Values (10-20) : Fewer signals, avoids whipsaws, suited for swing trading.
Lower Values (0-5) : More responsive, allows quick reversals, ideal for scalping.
Timeframes :
Scalping : 0-2 bars for rapid signals.
Day Trading : 3-5 bars for balance.
Swing Trading : 5-10 bars for stability.
Sectors :
Crypto : 0-3 for volatility.
Stocks : 5-10 for trend clarity.
Forex : 3-7 for cyclical moves.
Pro Tip : Increase in choppy markets to filter noise.
Hardcoded Parameters
Tropical, Motivic, Spectral, Perfectoid, Homotopy Inputs : Fixed to optimize performance but influence calculations (e.g., tropical_degree=4 for support levels, perfectoid_prime=5 for convergence).
Optimization : Experiment with codebase modifications if advanced customization is needed, but defaults are robust across markets.
🎨 ADVANCED VISUAL SYSTEM: TRADING IN A GEOMETRIC UNIVERSE
The GTTMTSF ’s visuals are direct representations of its mathematics, designed for intuitive and precise trading decisions.
Motivic Cohomology Bands :
What They Are : Dynamic bands ( H⁰ , H¹ , H² ) representing cohomological support/resistance.
Color & Meaning : Colors reflect energy levels ( H⁰ tightest, H² widest). Breaks into H¹ signal momentum; H² touches suggest reversals.
How to Trade : Use for stop-loss/profit-taking. Band bounces with Dashboard confirmation are high-probability setups.
Morphism Flow (Webbing) :
What It Is : White particle streams visualizing market momentum.
Interpretation : Dense flows indicate strong trends; sparse flows signal consolidation.
How to Trade : Follow dominant flow direction; new flows post-consolidation signal trend starts.
Future Projection Web (Fractal Grid) :
What It Is : Fibonacci-period fractal projections of support/resistance.
Color & Meaning : Three-layer lines (white shadow, glow, colored quantum) with labels showing price, topological class, anomaly strength (φ), resonance (ρ), and obstruction ( H¹ ). ⚡ marks extreme anomalies.
How to Trade : Target ⚡/● levels for entries/exits. High-anomaly levels with weakening Unified Field are reversal setups.
Holographic Mesh & Spectral Flow :
What They Are : Visuals of harmonic interference and spectral energy.
How to Trade : Bright mesh nodes or strong Spectral Flow warn of building pressure before price movement.
📊 THE GEOMETRIC DASHBOARD: YOUR MISSION CONTROL
The Dashboard translates complex mathematics into actionable intelligence.
Unified Field & Signals :
FIELD : Master value (-10 to +10), synthesizing all geometric components. Extreme readings (>5 or <-5) signal structural limits, often preceding reversals or continuations.
RESONANCE : Measures harmony between geometric field and price-volume momentum. Positive amplifies bullish moves; negative amplifies bearish moves.
SIGNAL QUALITY : Confidence meter rating alignment. Trade only STRONG or EXCEPTIONAL signals for high-probability setups.
Geometric Components :
What They Are : Breakdown of seven mathematical engines.
How to Use : Watch for convergence. A strong Unified Field is reliable when components (e.g., Grothendieck , Topos , Motivic ) align. Divergence warns of trend weakening.
Signal Performance :
What It Is : Tracks indicator signal performance.
How to Use : Assesses real-time performance to build confidence and understand system behavior.
🚀 DEVELOPMENT & UNIQUENESS: BEYOND CONVENTIONAL ANALYSIS
The GTTMTSF was developed to analyze markets as evolving geometric objects, not statistical time-series.
Why This Is Unlike Anything Else :
Theoretical Depth : Uses geometry and topology, identifying patterns invisible to statistical tools.
Holistic Synthesis : Integrates seven deep mathematical frameworks into a cohesive Unified Field .
Creative Implementation : Translates PhD-level mathematics into functional Pine Script , blending theory and practice.
Immersive Visualization : Transforms charts into dynamic geometric landscapes for intuitive market understanding.
The GTTMTSF is more than an indicator; it’s a new lens for viewing markets, for traders seeking deeper insight into hidden order within chaos.
" Where there is matter, there is geometry. " - Johannes Kepler
— Dskyz , Trade with insight. Trade with anticipation.
Topological Market Stress (TMS) - Quantum FabricTopological Market Stress (TMS) - Quantum Fabric
What Stresses The Market?
Topological Market Stress (TMS) represents a revolutionary fusion of algebraic topology and quantum field theory applied to financial markets. Unlike traditional indicators that analyze price movements linearly, TMS examines the underlying topological structure of market data—detecting when the very fabric of market relationships begins to tear, warp, or collapse.
Drawing inspiration from the ethereal beauty of quantum field visualizations and the mathematical elegance of topological spaces, this indicator transforms complex mathematical concepts into an intuitive, visually stunning interface that reveals hidden market dynamics invisible to conventional analysis.
Theoretical Foundation: Topology Meets Markets
Topological Holes in Market Structure
In algebraic topology, a "hole" represents a fundamental structural break—a place where the normal connectivity of space fails. In markets, these topological holes manifest as:
Correlation Breakdown: When traditional price-volume relationships collapse
Volatility Clustering Failure: When volatility patterns lose their predictive power
Microstructure Stress: When market efficiency mechanisms begin to fail
The Mathematics of Market Topology
TMS constructs a topological space from market data using three key components:
1. Correlation Topology
ρ(P,V) = correlation(price, volume, period)
Hole Formation = 1 - |ρ(P,V)|
When price and volume decorrelate, topological holes begin forming.
2. Volatility Clustering Topology
σ(t) = volatility at time t
Clustering = correlation(σ(t), σ(t-1), period)
Breakdown = 1 - |Clustering|
Volatility clustering breakdown indicates structural instability.
3. Market Efficiency Topology
Efficiency = |price - EMA(price)| / ATR
Measures how far price deviates from its efficient trajectory.
Multi-Scale Topological Analysis
Markets exist across multiple temporal scales simultaneously. TMS analyzes topology at three distinct scales:
Micro Scale (3-15 periods): Immediate structural changes, market microstructure stress
Meso Scale (10-50 periods): Trend-level topology, medium-term structural shifts
Macro Scale (50-200 periods): Long-term structural topology, regime-level changes
The final stress metric combines all scales:
Combined Stress = 0.3×Micro + 0.4×Meso + 0.3×Macro
How TMS Works
1. Topological Space Construction
Each market moment is embedded in a multi-dimensional topological space where:
- Price efficiency forms one dimension
- Correlation breakdown forms another
- Volatility clustering breakdown forms the third
2. Hole Detection Algorithm
The indicator continuously scans this topological space for:
Hole Formation: When stress exceeds the formation threshold
Hole Persistence: How long structural breaks maintain
Hole Collapse: Sudden topology restoration (regime shifts)
3. Quantum Visualization Engine
The visualization system translates topological mathematics into intuitive quantum field representations:
Stress Waves: Main line showing topological stress intensity
Quantum Glow: Surrounding field indicating stress energy
Fabric Integrity: Background showing structural health
Multi-Scale Rings: Orbital representations of different timeframes
4. Signal Generation
Stable Topology (✨): Normal market structure, standard trading conditions
Stressed Topology (⚡): Increased structural tension, heightened volatility expected
Topological Collapse (🕳️): Major structural break, regime shift in progress
Critical Stress (🌋): Extreme conditions, maximum caution required
Inputs & Parameters
🕳️ Topological Parameters
Analysis Window (20-200, default: 50)
Primary period for topological analysis
20-30: High-frequency scalping, rapid structure detection
50: Balanced approach, recommended for most markets
100-200: Long-term position trading, major structural shifts only
Hole Formation Threshold (0.1-0.9, default: 0.3)
Sensitivity for detecting topological holes
0.1-0.2: Very sensitive, detects minor structural stress
0.3: Balanced, optimal for most market conditions
0.5-0.9: Conservative, only major structural breaks
Density Calculation Radius (0.1-2.0, default: 0.5)
Radius for local density estimation in topological space
0.1-0.3: Fine-grained analysis, sensitive to local changes
0.5: Standard approach, balanced sensitivity
1.0-2.0: Broad analysis, focuses on major structural features
Collapse Detection (0.5-0.95, default: 0.7)
Threshold for detecting sudden topology restoration
0.5-0.6: Very sensitive to regime changes
0.7: Balanced, reliable collapse detection
0.8-0.95: Conservative, only major regime shifts
📊 Multi-Scale Analysis
Enable Multi-Scale (default: true)
- Analyzes topology across multiple timeframes simultaneously
- Provides deeper insight into market structure at different scales
- Essential for understanding cross-timeframe topology interactions
Micro Scale Period (3-15, default: 5)
Fast scale for immediate topology changes
3-5: Ultra-fast, tick/minute data analysis
5-8: Fast, 5m-15m chart optimization
10-15: Medium-fast, 30m-1H chart focus
Meso Scale Period (10-50, default: 20)
Medium scale for trend topology analysis
10-15: Short trend structures
20-25: Medium trend structures (recommended)
30-50: Long trend structures
Macro Scale Period (50-200, default: 100)
Slow scale for structural topology
50-75: Medium-term structural analysis
100: Long-term structure (recommended)
150-200: Very long-term structural patterns
⚙️ Signal Processing
Smoothing Method (SMA/EMA/RMA/WMA, default: EMA) Method for smoothing stress signals
SMA: Simple average, stable but slower
EMA: Exponential, responsive and recommended
RMA: Running average, very smooth
WMA: Weighted average, balanced approach
Smoothing Period (1-10, default: 3)
Period for signal smoothing
1-2: Minimal smoothing, noisy but fast
3-5: Balanced, recommended for most applications
6-10: Heavy smoothing, slow but very stable
Normalization (Fixed/Adaptive/Rolling, default: Adaptive)
Method for normalizing stress values
Fixed: Static 0-1 range normalization
Adaptive: Dynamic range adjustment (recommended)
Rolling: Rolling window normalization
🎨 Quantum Visualization
Fabric Style Options:
Quantum Field: Flowing energy visualization with smooth gradients
Topological Mesh: Mathematical topology with stepped lines
Phase Space: Dynamical systems view with circular markers
Minimal: Clean, simple display with reduced visual elements
Color Scheme Options:
Quantum Gradient: Deep space blue → Quantum red progression
Thermal: Black → Hot orange thermal imaging style
Spectral: Purple → Gold full spectrum colors
Monochrome: Dark gray → Light gray elegant simplicity
Multi-Scale Rings (default: true)
- Display orbital rings for different time scales
- Visualizes how topology changes across timeframes
- Provides immediate visual feedback on cross-scale dynamics
Glow Intensity (0.0-1.0, default: 0.6)
Controls the quantum glow effect intensity
0.0: No glow, pure line display
0.6: Balanced, recommended setting
1.0: Maximum glow, full quantum field effect
📋 Dashboard & Alerts
Show Dashboard (default: true)
Real-time topology status display
Current market state and trading recommendations
Stress level visualization and fabric integrity status
Show Theory Guide (default: true)
Educational panel explaining topological concepts
Dashboard interpretation guide
Trading strategy recommendations
Enable Alerts (default: true)
Extreme stress detection alerts
Topological collapse notifications
Hole formation and recovery signals
Visual Logic & Interpretation
Main Visualization Elements
Quantum Stress Line
Primary indicator showing topological stress intensity
Color intensity reflects current market state
Line style varies based on selected fabric style
Glow effect indicates stress energy field
Equilibrium Line
Silver line showing average stress level
Reference point for normal market conditions
Helps identify when stress is elevated or suppressed
Upper/Lower Bounds
Red upper bound: High stress threshold
Green lower bound: Low stress threshold
Quantum fabric fill between bounds shows stress field
Multi-Scale Rings
Aqua circles : Micro-scale topology (immediate changes)
Orange circles: Meso-scale topology (trend-level changes)
Provides cross-timeframe topology visualization
Dashboard Information
Topology State Icons:
✨ STABLE: Normal market structure, standard trading conditions
⚡ STRESSED: Increased structural tension, monitor closely
🕳️ COLLAPSE: Major structural break, regime shift occurring
🌋 CRITICAL: Extreme conditions, reduce risk exposure
Stress Bar Visualization:
Visual representation of current stress level (0-100%)
Color-coded based on current topology state
Real-time percentage display
Fabric Integrity Dots:
●●●●● Intact: Strong market structure (0-30% stress)
●●●○○ Stressed: Weakening structure (30-70% stress)
●○○○○ Fractured: Breaking down structure (70-100% stress)
Action Recommendations:
✅ TRADE: Normal conditions, standard strategies apply
⚠️ WATCH: Monitor closely, increased vigilance required
🔄 ADAPT: Change strategy, regime shift in progress
🛑 REDUCE: Lower risk exposure, extreme conditions
Trading Strategies
In Stable Topology (✨ STABLE)
- Normal trading conditions apply
- Use standard technical analysis
- Regular position sizing appropriate
- Both trend-following and mean-reversion strategies viable
In Stressed Topology (⚡ STRESSED)
- Increased volatility expected
- Widen stop losses to account for higher volatility
- Reduce position sizes slightly
- Focus on high-probability setups
- Monitor for potential regime change
During Topological Collapse (🕳️ COLLAPSE)
- Major regime shift in progress
- Adapt strategy immediately to new market character
- Consider closing positions that rely on previous regime
- Wait for new topology to stabilize before major trades
- Opportunity for contrarian plays if collapse is extreme
In Critical Stress (🌋 CRITICAL)
- Extreme market conditions
- Significantly reduce risk exposure
- Avoid new positions until stress subsides
- Focus on capital preservation
- Consider hedging existing positions
Advanced Techniques
Multi-Timeframe Topology Analysis
- Use higher timeframe TMS for regime context
- Use lower timeframe TMS for precise entry timing
- Alignment across timeframes = highest probability trades
Topology Divergence Trading
- Most powerful at regime boundaries
- Price makes new high/low but topology stress decreases
- Early warning of potential reversals
- Combine with key support/resistance levels
Stress Persistence Analysis
- Long periods of stable topology often precede major moves
- Extended stress periods often resolve in regime changes
- Use persistence tracking for position sizing decisions
Originality & Innovation
TMS represents a genuine breakthrough in applying advanced mathematics to market analysis:
True Topological Analysis: Not a simplified proxy but actual topological space construction and hole detection using correlation breakdown, volatility clustering analysis, and market efficiency measurement.
Quantum Aesthetic: Transforms complex topology mathematics into an intuitive, visually stunning interface inspired by quantum field theory visualizations.
Multi-Scale Architecture: Simultaneous analysis across micro, meso, and macro timeframes provides unprecedented insight into market structure dynamics.
Regime Detection: Identifies fundamental market character changes before they become obvious in price action, providing early warning of structural shifts.
Practical Application: Clear, actionable signals derived from advanced mathematical concepts, making theoretical topology accessible to practical traders.
This is not a combination of existing indicators or a cosmetic enhancement of standard tools. It represents a fundamental reimagining of how we measure, visualize, and interpret market dynamics through the lens of algebraic topology and quantum field theory.
Best Practices
Start with defaults: Parameters are optimized for broad market applicability
Match timeframe: Adjust scales based on your trading timeframe
Confirm with price action: TMS shows market character, not direction
Respect topology changes: Reduce risk during regime transitions
Use appropriate strategies: Adapt approach based on current topology state
Monitor persistence: Track how long topology states maintain
Cross-timeframe analysis: Align multiple timeframes for highest probability trades
Alerts Available
Extreme Topological Stress: Market fabric under severe deformation
Topological Collapse Detected: Regime shift in progress
Topological Hole Forming: Market structure breakdown detected
Topology Stabilizing: Market structure recovering to normal
Chart Requirements
Recommended Markets: All liquid markets (forex, stocks, crypto, futures)
Optimal Timeframes: 5m to Daily (adaptable to any timeframe)
Minimum History: 200 bars for proper topology construction
Best Performance: Markets with clear regime characteristics
Academic Foundation
This indicator draws from cutting-edge research in:
- Algebraic topology and persistent homology
- Quantum field theory visualization techniques
- Market microstructure analysis
- Multi-scale dynamical systems theory
- Correlation topology and network analysis
Disclaimer
This indicator is for educational and research purposes only. It does not constitute financial advice or provide direct buy/sell signals. Topological analysis reveals market structure characteristics, not future price direction. Always use proper risk management and combine with your own analysis. Past performance does not guarantee future results.
See markets through the lens of topology. Trade the structure, not the noise.
Bringing advanced mathematics to practical trading through quantum-inspired visualization.
Trade with insight. Trade with structure.
— Dskyz , for DAFE Trading Systems
MLExtensions_CoreLibrary "MLExtensions_Core"
A set of extension methods for a novel implementation of a Approximate Nearest Neighbors (ANN) algorithm in Lorentzian space, focused on computation.
normalizeDeriv(src, quadraticMeanLength)
Returns the smoothed hyperbolic tangent of the input series.
Parameters:
src (float) : The input series (i.e., the first-order derivative for price).
quadraticMeanLength (int) : The length of the quadratic mean (RMS).
Returns: nDeriv The normalized derivative of the input series.
normalize(src, min, max)
Rescales a source value with an unbounded range to a target range.
Parameters:
src (float) : The input series
min (float) : The minimum value of the unbounded range
max (float) : The maximum value of the unbounded range
Returns: The normalized series
rescale(src, oldMin, oldMax, newMin, newMax)
Rescales a source value with a bounded range to anther bounded range
Parameters:
src (float) : The input series
oldMin (float) : The minimum value of the range to rescale from
oldMax (float) : The maximum value of the range to rescale from
newMin (float) : The minimum value of the range to rescale to
newMax (float) : The maximum value of the range to rescale to
Returns: The rescaled series
getColorShades(color)
Creates an array of colors with varying shades of the input color
Parameters:
color (color) : The color to create shades of
Returns: An array of colors with varying shades of the input color
getPredictionColor(prediction, neighborsCount, shadesArr)
Determines the color shade based on prediction percentile
Parameters:
prediction (float) : Value of the prediction
neighborsCount (int) : The number of neighbors used in a nearest neighbors classification
shadesArr (array) : An array of colors with varying shades of the input color
Returns: shade Color shade based on prediction percentile
color_green(prediction)
Assigns varying shades of the color green based on the KNN classification
Parameters:
prediction (float) : Value (int|float) of the prediction
Returns: color
color_red(prediction)
Assigns varying shades of the color red based on the KNN classification
Parameters:
prediction (float) : Value of the prediction
Returns: color
tanh(src)
Returns the the hyperbolic tangent of the input series. The sigmoid-like hyperbolic tangent function is used to compress the input to a value between -1 and 1.
Parameters:
src (float) : The input series (i.e., the normalized derivative).
Returns: tanh The hyperbolic tangent of the input series.
dualPoleFilter(src, lookback)
Returns the smoothed hyperbolic tangent of the input series.
Parameters:
src (float) : The input series (i.e., the hyperbolic tangent).
lookback (int) : The lookback window for the smoothing.
Returns: filter The smoothed hyperbolic tangent of the input series.
tanhTransform(src, smoothingFrequency, quadraticMeanLength)
Returns the tanh transform of the input series.
Parameters:
src (float) : The input series (i.e., the result of the tanh calculation).
smoothingFrequency (int)
quadraticMeanLength (int)
Returns: signal The smoothed hyperbolic tangent transform of the input series.
n_rsi(src, n1, n2)
Returns the normalized RSI ideal for use in ML algorithms.
Parameters:
src (float) : The input series (i.e., the result of the RSI calculation).
n1 (simple int) : The length of the RSI.
n2 (simple int) : The smoothing length of the RSI.
Returns: signal The normalized RSI.
n_cci(src, n1, n2)
Returns the normalized CCI ideal for use in ML algorithms.
Parameters:
src (float) : The input series (i.e., the result of the CCI calculation).
n1 (simple int) : The length of the CCI.
n2 (simple int) : The smoothing length of the CCI.
Returns: signal The normalized CCI.
n_wt(src, n1, n2)
Returns the normalized WaveTrend Classic series ideal for use in ML algorithms.
Parameters:
src (float) : The input series (i.e., the result of the WaveTrend Classic calculation).
n1 (simple int)
n2 (simple int)
Returns: signal The normalized WaveTrend Classic series.
n_adx(highSrc, lowSrc, closeSrc, n1)
Returns the normalized ADX ideal for use in ML algorithms.
Parameters:
highSrc (float) : The input series for the high price.
lowSrc (float) : The input series for the low price.
closeSrc (float) : The input series for the close price.
n1 (simple int) : The length of the ADX.
regime_filter(src, threshold, useRegimeFilter)
Parameters:
src (float)
threshold (float)
useRegimeFilter (bool)
filter_adx(src, length, adxThreshold, useAdxFilter)
filter_adx
Parameters:
src (float) : The source series.
length (simple int) : The length of the ADX.
adxThreshold (int) : The ADX threshold.
useAdxFilter (bool) : Whether to use the ADX filter.
Returns: The ADX.
filter_volatility(minLength, maxLength, sensitivityMultiplier, useVolatilityFilter)
filter_volatility
Parameters:
minLength (simple int) : The minimum length of the ATR.
maxLength (simple int) : The maximum length of the ATR.
sensitivityMultiplier (float) : Multiplier for the historical ATR to control sensitivity.
useVolatilityFilter (bool) : Whether to use the volatility filter.
Returns: Boolean indicating whether or not to let the signal pass through the filter.
Quantum Motion Oscillator-QMO (TechnoBlooms)Quantum Motion Oscillator (QMO) is a momentum indicator designed for traders who demand precision. Combining multi-timeframe weighted linear regression with EMA crossovers, QMO offers a dynamic view of market momentum, helping traders anticipate trend shifts with greater accuracy.
This oscillator is inspired by quantum mechanics and wave theory, where market movement is seen as a series of probabilistic waves rather than rigid structures.
The histogram is plotted in proportion to the price movement of the candlesticks.
KEY FEATURES
1. Multi-Timeframe Histogram - Integrates 1 to 5 weighted linear regression averages, reducing lag while maintaining accuracy.
2. EMA Crossover Signal - Uses a Short and Long EMA to confirm trend shifts with minimal noise.
3. Adaptive Trend Analysis - Self-adjusting mechanics make QMO effective in both ranging and trending markets.
4. Scalable for Different Trading Styles - Works seamlessly for scalping, intraday, swing and position trading.
ADVANCED PROFESSIONAL INSIGHTS
1. Wave Dynamics and Market Flow - Inspired by wave mechanics, QMO reflects the energy accumulation and dissipation in price movements.
Expanding histogram waves = Strong momentum surge
Contracting waves = Momentum weakening, potential reversal zone.
2. Liquidity and Order Flow Applications - QMO works well alongside liquidity concepts and smart money techniques:
Combine with Fair Value Gaps & Order Blocks -> Enter when QMO signals align with liquidity zones.
Avoid False Moves - If price sweeps liquidity, but QMO momentum diverges, it is a sign of potential smart money manipulation.
SemiCircle Cycle Notation PivotsFor decades, traders have sought to decode the rhythm of the markets through cycle theory. From the groundbreaking work of HM Gartley in the 1930s to modern-day cycle trading tools on TradingView, the concept remains the same: markets move in repeating waves with larger cycles influencing smaller ones in a fractal-like structure, and understanding their timing gives traders an edge to better anticipate future price movements🔮.
Traditional cycle analysis has always been manual, requiring traders to painstakingly plot semicircles, diamonds, or sine waves to estimate pivot points and time reversals. Drawing tools like semicircle & sine wave projections exist on TradingView, but they lack automation—forcing traders to adjust cycle lengths by eye, often leading to inconsistencies.
This is where SemiCircle Cycle Notation Pivots indicator comes in. Semicircle cycle chart notation appears to have evolved as a practical visualization tool among cycle theorists rather than being pioneered by a single individual; some key influences include HM Gartley, WD Gann, JM Hurst, Walter Bressert, and RayTomes. Built upon LonesomeTheBlue's foundational ZigZag Waves indicator , this indicator takes cycle visualization to the next level by dynamically detecting price pivots and then automatically plotting semicircles based on real-time cycle length calculations & expected rhythm of price action over time.
Key Features:
Automated Cycle Detection: The indicator identifies pivot points based on your preference—highs, lows, or both—and plots semicircle waves that correspond to Hurst's cycle notation.
Customizable Cycle Lengths: Tailor the analysis to your trading strategy with adjustable cycle lengths, defaulting to 10, 20, and 40 bars, allowing for flexibility across various timeframes and assets.
Dynamic Wave Scaling: The semicircle waves adapt to different price structures, ensuring that the visualization remains proportional to the detected cycle lengths and aiding in the identification of potential reversal points.
Automated Cycle Detection: Dynamically identifies price pivot points and automatically adjusts offsets based on real-time cycle length calculations, ensuring precise semicircle wave alignment with market structure.
Color-Coded Cycle Tiers: Each cycle tier is distinctly color-coded, enabling quick differentiation and a clearer understanding of nested market cycles.
