Fourier Weighted Moving Average-(FWMA)Fourier Weighted Moving Average (FWMA)
About Fourier and His Theory
Joseph Fourier (1768–1830) was a French mathematician and physicist best known for his work on heat transfer and periodic functions. His most significant contribution to science is what we now call Fourier Analysis.
What Is Fourier's Theory?
Fourier’s theory states that:
Any repeating (periodic) signal or pattern can be broken down into a sum of simple sine and cosine waves.
This idea became the foundation of signal processing, modern physics, and data smoothing techniques — including those used in financial markets.
Key Concepts of Fourier’s Theory
1. Decomposition of Signals
Complex waveforms can be expressed as combinations of basic sine waves with different frequencies and amplitudes.
2. Frequency Domain View
Instead of viewing data in time (or price), you can analyze its frequency — how often certain movements repeat.
3. Smoothing and Filtering
By focusing only on certain frequencies (e.g., slower or longer cycles), Fourier methods allow you to filter out short-term noise and focus on the trend.
4. Applications in Finance
In trading, Fourier principles help design indicators that:
* Remove short-term market noise
* Emphasize dominant cycles
* Provide cleaner trend direction
Why It Matters for This Indicator
The Fourier Weighted Moving Average (FWMA) used in this indicator applies a custom weight derived from a sin² function, inspired by Fourier’s work on wave behavior. This gives more influence to the mid-section of the price data, making the average line smoother and more stable than traditional methods like SMA or EMA.
Unlike basic moving averages, the FWMA reacts to price changes more fluidly while reducing whipsaws, which is especially useful for trend-following strategies.
Input Settings and Controls
This section outlines all configurable fields and buttons available in the indicator, grouped for clarity:
Main Settings
* Source
Defines the price source used in the FWMA calculation. Options typically include close, open, hl2, etc.
* FWMA – 1 (Length)
Sets the period for the first Fourier Weighted Moving Average. Shorter lengths produce faster, more sensitive lines.
* FWMA – 2 (Length)
Sets the period for the second FWMA, typically used as a slower or long-term trend filter.
* Weight Epsilon
A small constant added to the weight formula to prevent division by zero and improve numeric stability in the FWMA formula.
Slope Sensitivity
* Slope Sensitivity (Bars)
This field defines the number of bars used to calculate the slope of each FWMA. The slope determines whether the line is rising or falling and is used to change the line color accordingly.
* Enable Slope Coloring (Toggle)
When enabled, both FWMA lines change color based on their slope:
* Positive slope = trend up color
* Negative slope = trend down color
If disabled, lines are shown in a neutral (gray) color.
Ribbon Settings (Group: Ribbon)
* Enable Ribbon for FWMA-2 (Toggle)
Turns the ribbon feature on or off. When enabled, the script plots two additional lines slightly above and below FWMA-2.
* Ribbon Thickness
Controls the line width of the ribbon above and below FWMA-2. Values from 1 to 100 are allowed, giving full control over ribbon visual prominence.
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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
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.
Rubotics TDI Top/Bottom Indicator**Rubotics TDI Top/Bottom Indicator (Rubots TDI T/B)**
This proprietary indicator integrates several technical analysis tools into one cohesive system to help traders identify potential top and bottom signals directly on the price chart. Unlike standard indicators that merely plot common metrics, this script uniquely fuses a custom moving average algorithm with established oscillators to enhance signal clarity and market timing.
**Core Components and Unique Features:**
- **Global Visual Settings:**
- Easily toggle visual elements (tables, background highlights) that display key metrics and trading setup information.
- Provides a detailed on-chart display of strategy data and essential trading parameters.
- **MAVW Calculation (Proprietary):**
- Computes a series of weighted moving averages using Fibonacci-inspired lengths (3, 5, 8, 13, 21, 34) to generate a dynamic moving average (MAVW).
- The MAVW line is color-coded—blue when trending upward, red when trending downward, and yellow when neutral—to offer an immediate visual cue of market direction.
- **RSI Module:**
- Calculates the RSI on a user-selected price source (default: close) with a customizable period (default: 14).
- Adjustable thresholds (default: 45 and 55) allow for fine-tuning of overbought and oversold conditions.
- **TDI Component:**
- Adapts the RSI into a dynamic channel using a simple moving average and a scaled standard deviation (multiplied by 1.6185) to form upper and lower bands.
- Incorporates both fast and slow moving averages (default periods: 2 and 7) with optional band filling to visually highlight momentum changes.
- **Note:** The TDI logic is based on public methodologies for converting RSI data into a dynamic indicator.
- **WaveTrend Oscillator:**
- Uses configurable channel and smoothing parameters to generate a WaveTrend line for additional momentum confirmation.
- The oscillator is used to further validate top and bottom signals by identifying overbought or oversold conditions.
- **Note:** The WaveTrend calculations are derived from widely available, public-domain techniques.
- **Signal Generation:**
- **Buy Signal:** Generated when the RSI is below its lower threshold, the TDI fast MA crosses above the lower band (with prior bar confirmation), the price is below the MAVW, and the WaveTrend indicates oversold conditions.
- **Sell Signal:** Generated when the RSI is above its upper threshold, the TDI fast MA crosses below the upper band (with prior bar confirmation), the price is above the MAVW, and the WaveTrend signals overbought conditions.
- Signals are visually marked on the chart with upward and downward triangles and accompanied by alert conditions.
- **Volume-Based Bar Coloring & Additional Visuals:**
- Colors price bars based on volume relative to a moving average to highlight the strength of moves.
- Provides background color changes and a dynamic table of key metric values (MAVW, RSI, TDI bands, WaveTrend) for real-time analysis.
**Customization and Originality:**
- Extensive input parameters allow traders to adjust each component to suit their trading style and market conditions.
- The unique combination of the proprietary MAVW calculation with traditional RSI, TDI, and WaveTrend elements creates a robust system for detecting market tops and bottoms.
- **Closed-Source Justification:**
This indicator is published as a closed-source script due to the proprietary enhancements integrated into the MAVW algorithm and signal generation logic. These unique modifications provide added value beyond standard public indicators.
TASC 2025.04 The Ultimate Oscillator█ OVERVIEW
This script implements an alternative, refined version of the Ultimate Oscillator (UO) designed to reduce lag and enhance responsiveness in momentum indicators, as introduced by John F. Ehlers in his article "Less Lag In Momentum Indicators, The Ultimate Oscillator" from the April 2025 edition of TASC's Traders' Tips .
█ CONCEPTS
In his article, Ehlers states that indicators are essentially filters that remove unwanted noise (i.e., unnecessary information) from market data. Simply put, they process a series of data to place focus on specific information, providing a different perspective on price dynamics. Various filter types attenuate different periodic signals within the data. For instance, a lowpass filter allows only low-frequency signals, a highpass filter allows only high-frequency signals, and a bandpass filter allows signals within a specific frequency range .
Ehlers explains that the key to removing indicator lag is to combine filters of different types in such a way that the result preserves necessary, useful signals while minimizing delay (lag). His proposed UltimateOscillator aims to maintain responsiveness to a specific frequency range by measuring the difference between two highpass filters' outputs. The oscillator uses the following formula:
UO = (HP1 - HP2) / RMS
Where:
HP1 is the first highpass filter.
HP2 is another highpass filter that allows only shorter wavelengths than the critical period of HP1.
RMS is the root mean square of the highpass filter difference, used as a scaling factor to standardize the output.
The resulting oscillator is similar to a bandpass filter , because it emphasizes wavelengths between the critical periods of the two highpass filters. Ehlers' UO responds quickly to value changes in a series, providing a responsive view of momentum with little to no lag.
█ USAGE
Ehlers' UltimateOscillator sets the critical periods of its highpass filters using two parameters: BandEdge and Bandwidth :
The BandEdge sets the critical period of the second highpass filter, which determines the shortest wavelengths in the response.
The Bandwidth is a multiple of the BandEdge used for the critical period of the first highpass filter, which determines the longest wavelengths in the response. Ehlers suggests that a Bandwidth value of 2 works well for most applications. However, traders can use any value above or equal to 1.4.
Users can customize these parameters with the "Bandwidth" and "BandEdge" inputs in the "Settings/Inputs" tab.
The script plots the UO calculated for the specified "Source" series in a separate pane, with a color based on the chart's foreground color. Positive UO values indicate upward momentum or trends, and negative UO values indicate the opposite.
Additionally, this indicator provides the option to display a "cloud" from 10 additional UO series with different settings for an aggregate view of momentum. The "Cloud" input offers four display choices: "Bandwidth", "BandEdge", "Bandwidth + BandEdge", or "None".
The "Bandwidth" option calculates oscillators with different Bandwidth values based on the main oscillator's setting. Likewise, the "BandEdge" option calculates oscillators with varying BandEdge values. The "Bandwidth + BandEdge" option calculates the extra oscillators with different values for both parameters.
When a user selects any of these options, the script plots the maximum and minimum oscillator values and fills their space with a color gradient. The fill color corresponds to the net sum of each UO's sign , indicating whether most of the UOs reflect positive or negative momentum. Green hues mean most oscillators are above zero, signifying stronger upward momentum. Red hues mean most are below zero, indicating stronger downward momentum.
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.
TASC 2025.02 Autocorrelation Indicator█ OVERVIEW
This script implements the Autocorrelation Indicator introduced by John Ehlers in the "Drunkard's Walk: Theory And Measurement By Autocorrelation" article from the February 2025 edition of TASC's Traders' Tips . The indicator calculates the autocorrelation of a price series across several lags to construct a periodogram , which traders can use to identify market cycles, trends, and potential reversal patterns.
█ CONCEPTS
Drunkard's walk
A drunkard's walk , formally known as a random walk , is a type of stochastic process that models the evolution of a system or variable through successive random steps.
In his article, John Ehlers relates this model to market data. He discusses two first- and second-order partial differential equations, modified for discrete (non-continuous) data, that can represent solutions to the discrete random walk problem: the diffusion equation and the wave equation. According to Ehlers, market data takes on a mixture of two "modes" described by these equations. He theorizes that when "diffusion mode" is dominant, trading success is almost a matter of luck, and when "wave mode" is dominant, indicators may have improved performance.
Pink spectrum
John Ehlers explains that many recent academic studies affirm that market data has a pink spectrum , meaning the power spectral density of the data is proportional to the wavelengths it contains, like pink noise . A random walk with a pink spectrum suggests that the states of the random variable are correlated and not independent. In other words, the random variable exhibits long-range dependence with respect to previous states.
Autocorrelation function (ACF)
Autocorrelation measures the correlation of a time series with a delayed copy, or lag , of itself. The autocorrelation function (ACF) is a method that evaluates autocorrelation across a range of lags , which can help to identify patterns, trends, and cycles in stochastic market data. Analysts often use ACF to detect and characterize long-range dependence in a time series.
The Autocorrelation Indicator evaluates the ACF of market prices over a fixed range of lags, expressing the results as a color-coded heatmap representing a dynamic periodogram. Ehlers suggests the information from the periodogram can help traders identify different market behaviors, including:
Cycles : Distinguishable as repeated patterns in the periodogram.
Reversals : Indicated by sharp vertical changes in the periodogram when the indicator uses a short data length .
Trends : Indicated by increasing correlation across lags, starting with the shortest, over time.
█ USAGE
This script calculates the Autocorrelation Indicator on an input "Source" series, smoothed by Ehlers' UltimateSmoother filter, and plots several color-coded lines to represent the periodogram's information. Each line corresponds to an analyzed lag, with the shortest lag's line at the bottom of the pane. Green hues in the line indicate a positive correlation for the lag, red hues indicate a negative correlation (anticorrelation), and orange or yellow hues mean the correlation is near zero.
Because Pine has a limit on the number of plots for a single indicator, this script divides the periodogram display into three distinct ranges that cover different lags. To see the full periodogram, add three instances of this script to the chart and set the "Lag range" input for each to a different value, as demonstrated in the chart above.
With a modest autocorrelation length, such as 20 on a "1D" chart, traders can identify seasonal patterns in the price series, which can help to pinpoint cycles and moderate trends. For instance, on the daily ES1! chart above, the indicator shows repetitive, similar patterns through fall 2023 and winter 2023-2024. The green "triangular" shape rising from the zero lag baseline over different time ranges corresponds to seasonal trends in the data.
To identify turning points in the price series, Ehlers recommends using a short autocorrelation length, such as 2. With this length, users can observe sharp, sudden shifts along the vertical axis, which suggest potential turning points from upward to downward or vice versa.
TASC 2025.01 Linear Predictive Filters█ OVERVIEW
This script implements a suite of tools for identifying and utilizing dominant cycles in time series data, as introduced by John Ehlers in the "Linear Predictive Filters And Instantaneous Frequency" article featured in the January 2025 edition of TASC's Traders' Tips . Dominant cycle information can help traders adapt their indicators and strategies to changing market conditions.
█ CONCEPTS
Conventional technical indicators and strategies often rely on static, unchanging parameters, which may fail to account for the dynamic nature of market data. In his article, John Ehlers applies digital signal processing principles to address this issue, introducing linear predictive filters to identify cyclic information for adapting indicators and strategies to evolving market conditions.
This approach treats market data as a complex series in the time domain. Analyzing the series in the frequency domain reveals information about its cyclic components. To reduce the impact of frequencies outside a range of interest and focus on a specific range of cycles, Ehlers applies second-order highpass and lowpass filters to the price data, which attenuate or remove wavelengths outside the desired range. This band-limited analysis isolates specific parts of the frequency spectrum for various trading styles, e.g., longer wavelengths for position trading or shorter wavelengths for swing trading.
After filtering the series to produce band-limited data, Ehlers applies a linear predictive filter to predict future values a few bars ahead. The filter, calculated based on the techniques proposed by Lloyd Griffiths, adaptively minimizes the error between the latest data point and prediction, successively adjusting its coefficients to align with the band-limited series. The filter's coefficients can then be applied to generate an adaptive estimate of the band-limited data's structure in the frequency domain and identify the dominant cycle.
█ USAGE
This script implements the following tools presented in the article:
Griffiths Predictor
This tool calculates a linear predictive filter to forecast future data points in band-limited price data. The crosses between the prediction and signal lines can provide potential trade signals.
Griffiths Spectrum
This tool calculates a partial frequency spectrum of the band-limited price data derived from the linear predictive filter's coefficients, displaying a color-coded representation of the frequency information in the pane. This mode's display represents the data as a periodogram . The bottom of each plotted bar corresponds to a specific analyzed period (inverse of frequency), and the bar's color represents the presence of that periodic cycle in the time series relative to the one with the highest presence (i.e., the dominant cycle). Warmer, brighter colors indicate a higher presence of the cycle in the series, whereas darker colors indicate a lower presence.
Griffiths Dominant Cycle
This tool compares the cyclic components within the partial spectrum and identifies the frequency with the highest power, i.e., the dominant cycle . Traders can use this dominant cycle information to tune other indicators and strategies, which may help promote better alignment with dynamic market conditions.
Notes on parameters
Bandpass boundaries:
In the article, Ehlers recommends an upper bound of 125 bars or higher to capture longer-term cycles for position trading. He recommends an upper bound of 40 bars and a lower bound of 18 bars for swing trading. If traders use smaller lower bounds, Ehlers advises a minimum of eight bars to minimize the potential effects of aliasing.
Data length:
The Griffiths predictor can use a relatively small data length, as autocorrelation diminishes rapidly with lag. However, for optimal spectrum and dominant cycle calculations, the length must match or exceed the upper bound of the bandpass filter. Ehlers recommends avoiding excessively long lengths to maintain responsiveness to shorter-term cycles.
Gaussian RSI For Loop [TrendX_]The Gaussian RSI For Loop indicator is a sophisticated tool designed for trend-following traders seeking to identify strong uptrends in the market. By integrating a Gaussian and Weighted-MA (GWMA) with the Relative Strength Index (RSI), this indicator employs a loop-based scoring system to provide clear signals for potential trading opportunities. The combination of Gaussian smoothing techniques and overbought/oversold filtering enhances the indicator's ability to capture significant price movements while reducing noise, making it an optimal choice for traders aiming to capitalize on robust upward trends.
💎 KEY FEATURES
Gaussian Weighted Moving Average (GWMA): Smooths price data to reduce noise and enhance responsiveness to significant price changes.
Filtered RSI: Applies the RSI to Gaussian-filtered data, allowing for more accurate momentum readings.
Wavetrend Analysis: Calculates the difference between the Filtered RSI and its short-term moving average, providing additional insights into momentum shifts.
Loop-Based Scoring System: Evaluates the strength and direction of uptrends through a systematic analysis of the Filtered RSI against defined thresholds.
⚙️ USAGES
Identifying Strong Uptrends: Traders can use this indicator to pinpoint periods of strong upward momentum, helping them make informed decisions about entering long positions and its exits.
Trend and Signal Confirmation: The Score confirms Long and Exit signals which traders can see through the Dots on the Gaussian RSI.
🔎 BREAKDOWN
Gaussian-Filtered Data:
The first component of the Gaussian RSI For Loop is the application of a GWMA to the sourced price data. This smoothing technique uses weighted averages based on a Gaussian distribution, which emphasizes more recent prices while diminishing the impact of older prices. This GWMA effectively reduces market noise, allowing traders to focus on significant price movements. By adjusting weights using sigma parameters, traders can fine-tune the sensitivity of the indicator, making it more responsive to genuine market trends while filtering out minor fluctuations that could lead to misleading signals.
Filtered RSI:
Next, the RSI is applied to the Gaussian-filtered data. The RSI measures the speed and change of price movements, providing insights into overbought or oversold conditions. By applying the RSI to smoothed price data, traders obtain a clearer view of momentum without the distortion caused by sudden price spikes or drops. This results in more reliable readings that help identify potential trend reversals or continuations.
Wavetrend Analysis:
The Wavetrend component calculates the difference between the Filtered RSI and its short-term moving average (MA). This difference serves as an additional momentum indicator. When the Filtered RSI is above its short-term MA, it suggests that upward momentum is strengthening; conversely, when it falls below, it indicates weakening momentum. This analysis helps traders confirm whether an uptrend is gaining strength or losing traction.
Loop-Based Scoring System:
Range Analysis: The system evaluates the Filtered RSI by comparing its current value against overbought (OB) and oversold (OS) thresholds over a defined range. This systematic approach ensures that each value within this range contributes to understanding overall trend strength.
Score Calculation: As the loop iterates through values within the defined range, it adjusts a score based on whether the current Filtered RSI and its previous values are higher or lower than established OB and OS levels. This scoring mechanism quantifies trend strength and direction.
Strong Uptrend Trigger: A strong uptrend signal is generated when the score exceeds a predefined Score Threshold (Long). This indicates that bullish momentum is robust enough to warrant entry into long positions.
None Trend: Conversely, if the score falls below the Score Threshold (Short), it suggests that upward momentum has weakened significantly, signaling potential exit points and it can be consolidated or downtrend.
DISCLAIMER
This indicator is not financial advice, it can only help traders make better decisions. There are many factors and uncertainties that can affect the outcome of any endeavor, and no one can guarantee or predict with certainty what will occur. Therefore, one should always exercise caution and judgment when making decisions based on past performance.
Bat Harmonic Pattern [TradingFinder] Bat Chart Indicator🔵 Introduction
The Bat Harmonic Pattern, created by Scott Carney in the 1990s, is a sophisticated tool in technical analysis, used to identify potential reversal points in price movements by leveraging Fibonacci ratios.
This pattern is classified into two primary types: the Bullish Bat Pattern, which signals the end of a downtrend and the beginning of an uptrend, and the Bearish Bat Pattern, which indicates the conclusion of an uptrend and the onset of a downtrend.
🟣 Bullish Bat Pattern
The Bullish Bat Pattern is designed to identify when a downtrend is likely to end and a new uptrend is about to begin. The key feature of this pattern is Point D, which typically aligns near the 88.6% Fibonacci retracement of the XA leg.
This point is considered a strong buy zone. When the price reaches Point D after a significant downtrend, it often indicates a potential reversal, presenting a buying opportunity for traders anticipating the start of an upward movement.
🟣 Bearish Bat Pattern
In contrast, the Bearish Bat Pattern forms when an uptrend is nearing its conclusion. Point D, which also typically aligns near the 88.6% Fibonacci retracement of the XA leg, serves as a critical point for traders.
This point is regarded as a strong sell zone, signaling that the uptrend may be ending, and a downtrend could be imminent. Traders often open short positions when they identify this pattern, aiming to capitalize on the anticipated downward movement.
🔵 How to Use
The Bat Pattern consists of five key points: X, A, B, C, and D, and four waves: XA, AB, BC, and CD. Fibonacci ratios play a crucial role in this pattern, helping traders pinpoint precise entry and exit points. In both the Bullish and Bearish Bat Patterns, the 88.6% retracement of the XA leg is a critical level for identifying potential reversal points.
🟣 Bullish Bat Pattern
Traders typically enter buy positions after Point D forms, expecting the downtrend to end and a new uptrend to start. This point, located near the 88.6% retracement of the XA leg, serves as a reliable buy signal.
🟣 Bearish Bat Pattern
Traders usually open short positions after identifying Point D, expecting the uptrend to end and a downtrend to begin. This point, also near the 88.6% retracement of the XA leg, acts as a valid sell signal.
🟣 Trading Tips for the Bat Pattern
Accurate Fibonacci Point Identification : Accurately identify Points X, A, B, C, and D, and calculate the Fibonacci ratios between these points. Point D should ideally be near the 88.6% retracement of the XA leg.
Signal Confirmation with Other Tools : To enhance the pattern's accuracy, avoid trading solely based on the Bat Pattern.
Risk Management : Always use stop-loss orders. In a Bullish Bat Pattern, place the stop-loss below Point X, and in a Bearish Bat Pattern, above Point X. This helps limit potential losses if the pattern fails.
Wait for Price Movement Confirmation : After identifying Point D, wait for the price to move in the anticipated direction to confirm the pattern's validity before entering a trade.
Set Realistic Profit Targets : Use Fibonacci retracement levels to set realistic profit targets, such as 38.2%, 50%, and 61.8% retracement levels of the CD leg. This strategy helps maximize profits and prevents premature exits.
🔵 Setting
🟣 Logical Setting
ZigZag Pivot Period : You can adjust the period so that the harmonic patterns are adjusted according to the pivot period you want. This factor is the most important parameter in pattern recognition.
Show Valid Forma t: If this parameter is on "On" mode, only patterns will be displayed that they have exact format and no noise can be seen in them. If "Off" is, the patterns displayed that maybe are noisy and do not exactly correspond to the original pattern.
Show Formation Last Pivot Confirm : if Turned on, you can see this ability of patterns when their last pivot is formed. If this feature is off, it will see the patterns as soon as they are formed. The advantage of this option being clear is less formation of fielded patterns, and it is accompanied by the latest pattern seeing and a sharp reduction in reward to risk.
Period of Formation Last Pivot : Using this parameter you can determine that the last pivot is based on Pivot period.
🟣 Genaral Setting
Show : Enter "On" to display the template and "Off" to not display the template.
Color : Enter the desired color to draw the pattern in this parameter.
LineWidth : You can enter the number 1 or numbers higher than one to adjust the thickness of the drawing lines. This number must be an integer and increases with increasing thickness.
LabelSize : You can adjust the size of the labels by using the "size.auto", "size.tiny", "size.smal", "size.normal", "size.large" or "size.huge" entries.
🟣 Alert Setting
Alert : On / Off
Message Frequency : This string parameter defines the announcement frequency. Choices include: "All" (activates the alert every time the function is called), "Once Per Bar" (activates the alert only on the first call within the bar), and "Once Per Bar Close" (the alert is activated only by a call at the last script execution of the real-time bar upon closing). The default setting is "Once per Bar".
Show Alert Time by Time Zone : The date, hour, and minute you receive in alert messages can be based on any time zone you choose. For example, if you want New York time, you should enter "UTC-4". This input is set to the time zone "UTC" by default.
🔵 Conclusion
The Bat Harmonic Pattern is a powerful tool in technical analysis, offering traders the ability to identify critical reversal points using Fibonacci ratios. By recognizing the Bullish and Bearish Bat Patterns, traders can anticipate potential trend reversals and make informed trading decisions.
However, it is essential to combine the Bat Pattern with other technical analysis tools and confirm signals for better trading outcomes. With proper use, this pattern can help traders minimize risk and optimize their entry and exit points in the market.
REV01 - Combined WT and SQZMOM Indicator and VWAP [KMARHOUMI]The Combined WaveTrend and Squeeze Momentum Indicator with VWAP (CWT_SQZMOM) is a powerful trading tool designed for traders looking to capitalize on market momentum and volatility squeezes, with the added insight of volume-weighted average price (VWAP) levels.
This custom indicator integrates three key components:
WaveTrend Oscillator: A momentum indicator that highlights potential reversal points in the market by identifying overbought and oversold conditions.
Squeeze
Momentum Indicator (SQZMOM): Identifies market consolidation periods (squeeze) and potential momentum breakouts, offering visual cues for significant price movements.
Volume-Weighted Average Price (VWAP): Provides a baseline measure of the average price based on volume, crucial for understanding market direction within a trading day.
Features
Visual Cues: Utilizes color-coded histograms, circles, and triangles to provide clear visual signals for trading opportunities.
Customizable Parameters: Allows traders to adjust input values for the WaveTrend Oscillator and Squeeze Momentum Indicator to fit various trading styles and timeframes.
Dynamic Indicators: Combines price momentum with volume data, offering a comprehensive view of market conditions.
How to Use
Setup: Apply the indicator to any chart in a trading platform that supports Pine Script (e.g., TradingView). Adjust the input parameters as needed to match your trading strategy and the asset's volatility.
Reading the Indicator:
WaveTrend Crossovers: Look for blue circles indicating a bullish crossover of the WaveTrend lines (wt1 crosses above wt2) and fuchsia circles for a bearish crossover (wt1 crosses below wt2). These points signal potential reversal opportunities.
Squeeze Momentum (SQZMOM): Green triangles at the bottom indicate a "Squeeze On" condition, suggesting market consolidation and potential for a breakout. Red triangles at the top signal a "Squeeze Off" condition, indicating the end of the squeeze and the start of a momentum phase.
VWAP: The price position relative to the VWAP line helps identify the overall market trend. Prices above VWAP may indicate bullish conditions, while prices below VWAP suggest bearish conditions.
Example Scenario for Going Long
Imagine the asset's price has been consolidating, and you observe a green triangle ("Squeeze On") at the bottom of the chart, indicating a potential breakout. Shortly after, a blue circle appears, signaling a bullish crossover in the WaveTrend Oscillator. If this crossover occurs above the VWAP line, it strengthens the signal for a long position. Traders might enter a long trade at this point, setting a stop loss below the recent low and a take profit at a previous resistance level or using a risk-reward ratio that suits their strategy.
ESZ2023 M1 SR v231019E-mini S&P 500 Futures ESZ2023 Contract Gann Support & Resistance
Description:
Support and resistance angles based on starting date and time stamp and ending date and time stamp, extended to the right in time to show interaction with price. The method of drawing these Gann angles is different than other previously published “Gann angles” and uses an esoteric WD Gann time & price squaring calculation method that he never explicitly published but hid in plain sight in his book " Tunnel Thru the Air ". In the spirit of preserving the originality of Gann’s work, the underlying logic is not being explicitly disclosed here, only an expression of the logic derived from a ‘key’ he left us in his book.
Gann's methods were originally meant for position trading and swing trading larger timeframes. Here these Gann support and resistance levels have been adapted for intraday on the 1-minute chart.
While Gann’s method of calculating support and resistance levels works on any timeframe and instrument, these specific levels published have been calculated for the E-mini S&P 500 Futures ESZ2023 Contract.
What the script does, how it does it and how to use it:
This script draws angles on a chart that represent likely areas where price will encounter support or resistance according to what Gann called the “law of vibration”, suggesting that every instrument moved within its own vibrational frequency.
Gann’s law of vibration can be expressed on a chart as ripples created in still water are expressed by applying surface tension on the water to create the ripples. Similarly, to ripples in water, Gann’s price impulse waves cause price oscillation or ‘ripples’ that resonate through time. These support and resistance levels were calculated based on a single impulse wave in time. The angles represent where time and price square out relative to the impedance of the originating impulse wave.
To use the script, simply apply it to an ES chart on the 1-minute time frame. For improved readability, you should apply a dark theme to your chart. To troubleshoot instances where the lines won’t show for whatever reason, try refreshing the browser or re-applying the script. Panning backwards on the chart to where the line angles start will also get the angle lines to reappear.
What the Different Lines Mean:
Red – These are called ‘axis’ lines and represent very critical support and resistance levels that can signal major trend changes. The axis lines stem from a single impedance point of origin.
Yellow – These are called ‘node’ lines and represent minor support and resistance levels that can signal where price will target or retrace to as it moves towards a higher timeframe price objective. Nodal lines stem from an upper and lower node relative to the wave’s impedance center.
Preserving the Originality of the Script and Usefulness of the Lines Code:
The script dates and timestamps are being protected to deter the proliferation of tampered versions of these Gann calculations which will detract from their usefulness and make it harder for other TradingView users to find the original publisher source.
Consolidation Range Tracker[Trendoscope]🎲 Introducing Consolidation Range Tracker: Visualising Price Consolidation after Impulsive Moves
ConsolidationRangeTracker is an innovative indicator designed to assist traders in identifying and tracking price consolidation zones following impulsive market moves. This indicator is built on Auto Motive Wave indicator and Interactive Motive Wave indicator. This is also an attempt to plot Wyckoff Distribution pattern. But, instead of implying the price movement after consolidation, we are just leaving it to the interpretation of the users.
🎲 Process
Find impulse wave using the methods defined in Auto Motive Wave indicator and Interactive Motive Wave indicator
Define the range of consolidation based on predefined ratio (available as input settings)
Track the price movement within range along with number of bars and cumulative volume.
When price breaks out of the range, check if price ranged long enough to consider it as consolidation.
Retain the drawings and visualisation if the consolidation is confirmed before the breakout. Or else, remove them from the chart to keep it clean.
Overall output can be visualised as
Note : Patterns will not be there on the chart every time. It is normal for indicator not to show any drawings or patterns on the chart.
🎲 Stages of the Indicator
🎯 When an Impulse is formed
When an impulse wave is detected, wave is drawn on the chart along with details such as number of bars and volume spawning the impulse wave and the calculated range based on the input value. An alert of new impulse is also triggered if configured for alerts.
🎯 When an Impulse is updated
When price extends further without consolidating, the impulse wave is also updated to consider the latest values. This repaint is expected and as designed. We will also trigger an alert related to update of an impulse wave.
🎯 Update of range as and when it happens
Range is not bound and it keeps moving based on the highest and lowest price. Value of range is constant and it is calculated based on certain ratio of impulse as configured in settings. But, this range can move up and down based on which direction the price moves.
For example, this is the initial range when the impulse wave is formed.
But, after certain bars, we can see that the range shift slightly up because, price has more upward movement than downward.
No alerts are triggered during this phase.
🎯 Confirmed consolidation
Consolidation range is confirmed after price range through certain bars with respect to number of bars involved in the impulse wave. The default setting of 1 for range bar ratio means that range is confirmed when price ranges for same number of bars as that of impulse.
An alert is triggered when consolidation range is confirmed.
🎯 Breakout
Breakout happen if the price exceeds the range bracket. Breakout may happen either before or after confirmation of consolidation. In either case, an alert is triggered.
Patterns are removed from the chart if the consolidation is not confirmed. In other words, the price did not stay in range for long time.
🎲 Settings
Simple settings to define the zigzag base and few pattern related configuration.
🎲 Alerts
Alerts are configured using alert function and are triggered in following scenarios.
A new impulse created
An impulse wave is updated
Consolidation range confirmed
Breakout with/without confirmed consolidation.
🎲 Use Cases
Indicator can be used for identifying few types of patterns on the chart. But, they may involve user's discretion. Major patterns that can be identified are:
🎯 Flag Formation Consolidation after an impulse can be termed as flag and is a sign of trend continuation after consolidation.
🎯 Wyckoff Distribution Long consolidation with high volume after an impulse can be a sign of wyckoff distribution formation. This pattern is trend reversal pattern.
Conditional Chart Pattern Signals: ABC Top/BottomCCPS ABC is a set of top/bottom patterns based on three points.
Pattern Variants/Subvariants:
• UHV (Uphill Middle): The price retreats slightly and reverses to climb higher with V-shape. A downward signal of this variant points out the candle where the price might retreat again. Nonetheless, as it has been a strong uptrend with higher velocity and higher wave, the probability of a huge decrease is small. Thus, it is classified as a weak bearish signal and we should only use it as a warning, i.e., we will enter a sell position when there is another high with another bearish signal. Subvariant: UHV3.
• UHL (Uphill Top Left): When the price crawls near the top of a hill, it is higher and higher but the velocity and the wave decrease. Subvariants: UHL1 (only velocity decreases), UHL2 (only wave decreases), UHL3 (both velocity and wave decrease).
• DHC (Downhill Top Center): An increase followed by a decrease in price with higher velocity and higher wave represents the start of falling from the top of a hill. Subvariants: DHC1 (only velocity increases), DHC2 (only wave increases), DHC3 (both velocity and wave increase).
• DHR (Downhill Top Right): A small decrease followed by a larger decrease in price with higher velocity and higher wave represents the confirmation of falling from the top of a hill. Subvariants: DHR1 (only velocity increases), DHR2 (only wave increases), DHR3 (both velocity and wave increase).
• DHV (Downhill Middle): A large decrease followed by a small increase in price to form a V-shape with lower velocity yet higher wave represents the continuation of falling in the downside of a hill. Subvariant: DHV3.
• DVA (Downvalley Middle): The price gains slightly and reverses to plunge lower with A-shape. An upward signal of this variant points out the candle where the price might bounce again. Nonetheless, as it has been a strong downtrend with higher velocity and higher wave, the probability of a huge increase is small. Thus, it is classified as a weak bullish signal and we should only use it as a warning, i.e., we will enter a buy position when there is another low with another bullish signal. Subvariant: DVA3.
• DVL (Downvalley Bottom Left): When the price arrives near the bottom of a valley, it is lower and lower but the velocity and the wave decrease. Subvariants: DVL1 (only velocity decreases), DVL2 (only wave decreases), DVL3 (both velocity and wave decrease).
• UVC (Upvalley Bottom Center): A decrease followed by an increase in price with higher velocity and higher wave represents the start of rising from the bottom of a valley. Subvariants: UVC1 (only velocity increases), UVC2 (only wave increases), UVC3 (both velocity and wave increase).
• UVR (Upvalley Bottom Right): A small increase followed by a larger increase in price with higher velocity and higher wave represents the confirmation of rising from the bottom of a valley. Subvariants: UVR1 (only velocity increases), UVR2 (only wave increases), UVR3 (both velocity and wave increase).
• UVA (Upvalley Middle): A large increase followed by a small decrease in price to form an A-shape with lower velocity yet higher wave represents the continuation of rising in the upside of a valley. Subvariant: UVA3.
Wave Calculation:
• Full: Waves are calculated at middle and two edges. Forward: Waves are calculated at middle and right edge.
• Average: Waves are measured by average heights. Max: Waves are measured by max heights.
Bullish/Bearish Signal Candle Check: None/Standard/TL.
• None: Not check signal candle if it is bullish or bearish.
• Standard: Bullish candle if close is higher than open or close is higher than previous close.
• TL(c): Bullish/bearish candles follow the proprietary standard. It has more conditions than Standard.
Exit: Choose an exit mode to calculate historical performance.
• Next Occurrence: Exit of an occurrence stands at the next occurrence.
• Near Fixed Length: Exit of an occurrence stands at either a specified fixed length or the next occurrence depending on which one happens first.
Signal Label Text: Subvariant name/abbreviation.
Signal Label Tooltip:
• Total: Number of occurrences of the subvariant, including the current one.
• Entry Price ($): Close price of the signal.
• Max Profit ($): Max profit of an occurrence is calculated from after the signal until the next occurrence of the same subvariant.
• Min/Max/Average Max Profit ($): Min/max/average profit of a subvariant is calculated by getting min/max/average of max profit of all occurrences of that subvariant.
• Max Loss ($): Max loss of an occurrence is calculated from after the signal until the next occurrence of the same subvariant.
• Min/Max/Average Max Loss ($): Min/max/average loss of a subvariant is calculated by getting max/min/average of max loss of all occurrences of that subvariant.
• Win: Number of historical winning occurrences of the subvariant. An occurrence of a subvariant is defined as winning when the max profit is larger than the absolute value of the max loss.
• Min Length: Min time between occurrences of the subvariant in terms of candles.
• Max Length: Max time between occurrences of the subvariant in terms of candles.
• Average Length: Average time between occurrences of the subvariant in terms of candles.
Current Label Text: Shows information of the latest occurrence of each subvariant next to the current candle.
• Last Occurrence: Date/time in exchange timezone of the latest occurrence.
Specification & Performance:
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Usage:
Enter right when the signal closes or at the open of the next candle after the signal.
Other Features:
• Non-repainting.
• Compact design.
Markets: Developed and tested on: US100. Timeframes: Developed and tested on: 30m.
Trend & Pullback Toolkit (Expo)█ Overview
The Trend & Pullback Trading Toolkit is an all-encompassing suite of tools designed for serious traders who want a comprehensive trend approach. It empowers traders to align their strategies with prevailing market trends, thereby mitigating risk while maximizing profit potential.
The Toolkit helps traders spot, analyze, and react to market trends, pullbacks, and significant trends. It combines multiple trading methodologies, such as the Elliott Wave theory, cyclical analysis, retracement analysis, strength analysis, volatility analysis, and pivot analysis, to provide a thorough understanding of the market. All these tools can help traders detect trends, pullbacks, and major shifts in the overall trend. By integrating different methodologies, this toolkit offers a multifaceted approach to analyzing market trends.
In essence, the Trend & Pullback Toolkit is the complete package for traders seeking to detect, evaluate, and act upon market trends and pullbacks while being prepared for major trend shifts.
The Trend & Pullback Toolkit works in any market and timeframe for discretionary analysis and includes many oscillators and features, but first, let us define what a cycle is:
█ What is a cycle
This involves the analysis of recurring patterns or events in the market that repeat over a specific period. Cycles can exist in various time frames and can be identified and analyzed with various tools, including some types of oscillators or time-based analysis methods.
Traders must also be aware that cycles do not always repeat perfectly and can often shift, evolve, or disappear entirely.
█ Features & How They Work
Elliott Wave Cycles: This is a method of technical analysis that traders use to analyze financial market cycles and forecast market trends. Elliott Wave theory asserts that markets move in repetitive cycles, which traders can analyze to predict future price movement. The core principle behind the theory is that market prices alternate between an impulsive, or driving phase, and a corrective phase on all time scales of trend. This pattern forms a fractal, meaning it's a self-similar pattern that repeats regardless of the degree or size of the waves.
The Elliott Wave Cycle Feature uses the principle of the Elliott Wave to identify trends and pullbacks in real-time.
Ratio Wave Cycle: This method elaborates on the concept of how negative volatility, or the degree of variation in the negative returns of a financial instrument, influences the effectiveness of a relative price move. Essentially, it delves into the relationship between the negative fluctuations in the market and the resulting relative price change, exploring how the two aspects interact with each other.
The central concept is that trends are generally more stable and predictable than rapid retracements. Therefore, the indicator calculates the relationship between these two market movements. By doing so, it establishes a trend-based identification system. This system aids in forecasting future market movements, allowing traders to make informed decisions based on these predictions. Essentially, it uses the calculated relationship to discern the overall direction (trend) of the market despite temporary counter-movements (retracements), thereby providing a more robust trading signal.
Periodic Wave Cycle: Thi refers to patterns or events in price action that recur over a specific time period. Periodic cycles can range from short-term intraday cycles (like the tendency for stock market volatility to be high at the opening and close of trading) to long-term cycles trend cycles. Traders use this to predict future price movements and trends.
By identifying the phases of a cycle, traders can predict key turning points in the market.
Retracement Cycles: Retracements are temporary price reversals that occur within a larger trend. These retracements are a common occurrence in all markets and timeframes, representing a pause or counter-move within a larger prevailing trend. Retracements can be driven by a variety of factors, including profit-taking, market uncertainty, or a change in market fundamentals. Despite these periodic reversals, the overall trend (upwards or downwards) often continues after the retracement is complete.
Fibonacci retracement functions are primarily used to identify potential retracement levels.
Volatility Cycle: A volatility cycle refers to the periodic changes in the degree of dispersion or variability of a security's returns, expressed as a standard deviation or variance. This feature uses both measures.
Strength Cycle: Gauges the power of a market trend and its inherent impulses. This feature offers a broad perspective on the cyclical nature of markets, which alternate between periods of strength, often referred to as bull markets, and periods of weakness, known as bear markets. It effectively tracks the direction, intensity, and cyclic patterns of market behavior.
Let us define the difference between strength and impulse:
Strength: This refers to the power or force behind a price move. In trading, this refers to the momentum or volume supporting a price move.
Impulse: In the context of trading, an impulse usually refers to a strong move in price. Impulse moves are typically followed by corrective moves against the trend.
Pivot Cycles: Pivot cycles refer to the observation of recurring price patterns or turning points in the market. Pivots can be defined as significant highs or lows that act as potential reversal or support/resistance points. Pivot point analysis helps traders understand the prevailing market sentiment. Overall, pivot cycles provide traders with a framework to identify potential market turning points and price levels of interest.
█ How to use the Trend & Pullback Toolkit
Elliott Wave Cycles
Ratio Wave Cycle
Periodic Wave Cycle
Retracement Cycles
Volatility Cycle:
Strength Cycle
Pivot Cycles
█ Why is this Trend & Pullback Toolkit Needed?
The core philosophy of this toolkit revolves around the popular adage in trading circles: "The trend is your friend." This toolkit ensures that you are always in sync with the trend, thereby increasing the chances of successful trades.
Here's an overview of the key benefits:
Trend Identification: The toolkit includes sophisticated algorithms and indicators that help identify the prevailing trend in the market. These algorithms analyze price patterns, momentum, volume, and other factors to determine the direction and strength of the trend.
Risk Reduction: By enabling traders to trade with the trend, this toolkit reduces the risk of betting against market momentum.
Profit Maximization: Trading with the trend increases the likelihood of successful trades.
Advanced Analysis Tools: The toolkit includes tools that provide a deeper insight into market dynamics. These tools enable a multi-dimensional analysis of market trends, from Elliott Wave cycles and period cycles to retracement cycles, ratio wave cycles, pivot cycles, and strength cycles.
User-friendly Interface: Despite its sophistication, the toolkit is designed with user-friendliness in mind. It allows for customization and presents data in easy-to-understand formats.
Versatility: The toolkit is versatile and can be used across different markets - stocks, forex, commodities, and cryptocurrencies. This makes it a valuable resource for all types of traders.
█ Any Alert Function Call
This function allows traders to combine any feature and create customized alerts. These alerts can be set for various conditions and customized according to the trader's strategy or preferences.
█ In conclusion, The Trading Toolkit is a powerful ally for any trader, offering the capabilities to navigate the complexities of the market with ease. Whether you're a novice or an experienced trader, this toolkit provides a structured and systematic approach to trading.
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Disclaimer
The information contained in my Scripts/Indicators/Ideas/Algos/Systems does not constitute financial advice or a solicitation to buy or sell any securities of any type. I will not accept liability for any loss or damage, including without limitation any loss of profit, which may arise directly or indirectly from the use of or reliance on such information.
All investments involve risk, and the past performance of a security, industry, sector, market, financial product, trading strategy, backtest, or individual's trading does not guarantee future results or returns. Investors are fully responsible for any investment decisions they make. Such decisions should be based solely on an evaluation of their financial circumstances, investment objectives, risk tolerance, and liquidity needs.
My Scripts/Indicators/Ideas/Algos/Systems are only for educational purposes!
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