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Oheiya MFI + MWThis is a combination of Money Flow Index and Momentum wave with refined values and logic.
WaveTrend Momentum (Zeiierman)█ Overview
WaveTrend Momentum (Zeiierman) reveals the underlying rhythm of market movement through positive and negative momentum waves that visualize both sides of trend behavior. This dual-wave structure makes it easy to see how impulses and retracements interact in real time, helping you distinguish between a normal pullback within strength and the early signs of a trend losing momentum.
The indicator layers its waves with higher-timeframe trend alignment and adaptive context filters, mapping when momentum expands, when it fades, and where a pullback is approaching exhaustion or renewed trend strength is likely to emerge.
⚪ Why This One Is Unique
Unlike conventional wave oscillators, this design uses dual, phase-managed wave construction with adaptive scaling across symbols and timeframes. At its core is a three-mode Trend Strength engine (Adaptive, Stability, Structure) that dynamically adjusts to market conditions, supported by higher-timeframe regime sourcing and a dedicated impulse-and-divergence framework.
█ Main features
⚪ WaveTrend Momentum Waves
The foundation of the indicator lies in its ability to build positive and negative momentum waves that visualize both sides of market movement. This dual-wave structure makes it easy to identify trend direction, impulses, retracements, and exhaustion in real time, showing how momentum evolves within broader market phases. The waves can be used directly to gauge trend strength and direction, helping traders stay aligned with prevailing momentum or recognize when a shift is forming.
⚪ Extreme Moves
Extreme Zones highlight points where momentum reaches statistically stretched conditions, areas where price action often pauses, rebalances, or reverses. These zones help traders anticipate potential exhaustion before it becomes visible on price, improving timing for entries, exits, and scaling decisions.
⚪ Impulse Moves
Impulse Markers identify bursts of directional momentum, moments when trend energy expands sharply. These points often align with breakouts, accelerations, or continuation signals, helping traders focus on active opportunities rather than noise or consolidation.
⚪ Trend Strength
The Trend Strength Line adapts dynamically to shifting market regimes. It can operate in three modes: Adaptive, Stability, and Structure, each offering a different sensitivity level to trend changes. This feature helps confirm whether the trend is building, stabilizing, or losing strength, and serves as a foundation for bias filtering or trade direction confirmation.
⚪ Higher-Timeframe Trend Alignment
Integrates a higher-timeframe trend reference directly into the analysis, giving each wave context. This alignment clarifies when local pullbacks occur in harmony or conflict with the broader trend, making it easier to distinguish temporary corrections from true reversals.
⚪ Divergence Engine
A fully integrated divergence detection system that automatically spots both regular and hidden divergences between price and momentum. By surfacing early signs of trend weakening or continuation potential, it gives traders a structured way to detect subtle momentum shifts before they manifest in price.
█ How to Use
⚪ Trend Trading
WaveTrend Momentum excels as a trend-following framework by combining wave direction, Trend Strength, and higher-timeframe alignment to reveal when momentum is expanding or contracting within the broader market phase.
Note: To get trend waves, consider increasing the Wave Transition value to above 40.
Bullish WaveTrend Trend: When the positive momentum waves are above the neutral midpoint, the market is trending upward. Minor downward retracements within this structure often resolve back into trend continuation once buying pressure reasserts itself, particularly when the higher-timeframe context confirms a bullish regime.
Bearish WaveTrend Trend: When the negative wave dominates and remains below the midpoint, downside momentum controls the market. Minor upward retracements within this structure often resolve back into trend continuation once selling pressure reasserts itself, particularly when the higher-timeframe context confirms a bearish regime.
Bullish Trend Strength Line: A Trend Strength Line positioned above the midline indicates a bullish trend. A rising line reflects growing momentum and persistent buying pressure. The steeper the slope, the stronger the current regime. As long as the line continues to rise alongside positive waves, the trend remains structurally intact.
Bearish Trend Strength Line: A Trend Strength Line positioned below the midline indicates a bearish trend. A declining line reflects increasing selling pressure and persistent downside momentum. The steeper the slope, the stronger the current bearish regime. As long as the line continues to fall alongside negative waves, the trend remains structurally intact.
⚪ Momentum Trading
Momentum trading focuses on capturing the energy and force behind price movement, identifying whether the market is accelerating, losing steam, or preparing for a reversal. Momentum shifts can reveal temporary exhaustion, trend-strength continuation, or breakout acceleration before price action fully confirms it.
The indicator includes several features designed to detect and visualize momentum:
Waves: The core element of the indicator. The size and slope of the waves reflect the strength of momentum. Expanding waves indicate strong directional pressure, while contracting waves suggest cooling or consolidation.
Extreme Zones: When waves reach or exceed the extreme levels, the market enters statistically stretched conditions, signaling potential exhaustion or reversal zones. However, these events can also occur during strong trends, indicating continued strength in that direction. Market context is essential to determine whether an extreme should be interpreted as a reversal signal or as confirmation of trend momentum.
Impulse Markers: Highlight sudden bursts of momentum, often associated with breakouts or continuation events. Like Extreme Zones, Impulse Markers can appear within both reversals and strong trending phases. Context from price structure and higher timeframes helps identify whether the impulse reflects a trend-strength expansion or the final surge before exhaustion.
You can use any of these features to identify:
Breakouts: When Impulse or Extreme Markers align with expanding waves.
Reversals: When momentum reaches extreme levels followed by a fade in strength, it signals potential exhaustion before a structural shift. However, strong trends can also produce temporary fades that quickly recover, so context is key to distinguishing between true reversals and brief pauses within the trend.
⚪ Pullback Trading
Pullbacks represent short pauses or retracements within a prevailing trend. The combination of the Wave, Impulse Markers, and the Trend Strength Line helps identify when a pullback is maturing and when continuation is likely to resume.
Bullish WaveTrend and Trend Strength Pullback
In an uptrend, a brief dip in the negative wave, paired with a bullish Trend Strength, typically signals a healthy pullback rather than a reversal. When the negative wave begins to turn upward again, it confirms momentum recovery and potential for continuation.
Bearish WaveTrend and Trend Strength Pullback
In a downtrend, a short-lived rise in the positive wave while Trend Strength remains negative usually signals a counter-trend rally within weakness. As the positive wave fades and the negative wave expands again, downside continuation becomes more probable.
⚪ Divergence Trading
Divergence trading focuses on identifying moments when price and momentum move out of sync, signaling a potential shift in market direction or a slowdown in trend strength. These divergences often appear before reversals, consolidations, or major transitions in structure, making them a valuable early warning tool for traders.
The integrated Divergence Engine automatically detects these imbalances between price action and momentum. When price continues to move in one direction but momentum begins to fade, it suggests that the underlying strength driving the move is weakening.
█ How It Works
⚪ Wave Construction
The momentum wave is derived from phase-managed price smoothers, then normalized and bounded to express both positive and negative momentum within a single coherent structure.
Calculation: Composite moving frameworks with phase management, nonlinear rescaling, and amplitude companding to stabilize wave height and maintain consistent sensitivity.
⚪ Extremes
An auxiliary equilibrium tracker measures deviations from a dynamic mean to identify statistically stretched conditions in which momentum may begin to rebalance.
Calculation: Robust deviation mapping of a smoothed equilibrium series with adaptive thresholds for regime-consistent extremes.
⚪ Trend Strength Core
A tri-mode core measures directional persistence and adapts dynamically to changing market regimes, with optional higher-timeframe sourcing for context.
Calculation: Return-aggregated momentum with envelope gating (Adaptive), stability-biased curvature tracking (Stability), and structure-driven range midpoint logic (Structure).
⚪ Range & Regime Filter
A volatility-adjusted filter produces a smoothed state line and internal bias zones, allowing the indicator to contextualize momentum behavior within current volatility conditions.
Calculation: Volatility-normalized range synthesis with slow/fast quantization modes and optional smoothing to mitigate market chop.
⚪ Impulse Detection
Detects short-term bursts of directional energy and marks them as impulse events. These impulses highlight when momentum rapidly expands, often signaling breakouts, accelerations, or the end of low-volatility phases.
Calculation: Nonlinear impulse-response mapping that emphasizes higher-order rate changes while filtering out micro-noise.
⚪ Divergence Engine (Regular & Hidden)
Compares price swings against the wave’s momentum structure to identify early disagreement between price and internal strength.
Calculation: Swing-logic comparators analyze price relative to normalized wave amplitude to detect momentum shifts and potential divergence setups.
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Disclaimer
The content provided in my scripts, indicators, ideas, algorithms, and systems is for educational and informational purposes only. It does not constitute financial advice, investment recommendations, or a solicitation to buy or sell any financial instruments. 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.
付費腳本
Wave Analyzer - Bobal [hamgkia]The Bobal tool is a volume-based wave analyzer designed to highlight the effort behind price movement within trend waves. It is built with a focus on clarity, speed of response, and a Wyckoff-inspired philosophy, where volume and trend direction are deeply intertwined.
This script offers a unique visualization of directional volume flow — up or down — in clearly segmented waves, allowing traders to assess who is in control and how strong their effort is. It does this by calculating dynamic trend waves, accumulating volume within those waves, and comparing volume to volatility for normalization.
🔶 WHAT'S INCLUDED
Detects directional waves based on your selected moving average (SMA, EMA, WMA, or HMA).
Accumulates volume within each wave, creating a distinct "volume block" per wave.
Normalizes volume by ATR (optional) to adjust for current market volatility.
Applies a power function to volume strength for dynamic contrast (stronger waves stand out visually).
Plots volume histograms in real-time: green/orange for up waves, red/fuchsia for down waves.
Optional - displays trend strength background based on recent price expansion vs ATR.
🔷 HOW IT WORKS
Wave Definition
A wave is defined as a sequence of bars moving in the same direction based on a selected moving average:
If the MA rises → uptrend wave
If the MA falls → downtrend wave
Wave resets on direction change.
Volume Accumulation
Volume is accumulated within each wave, starting fresh at the beginning of each new wave. This clean segmentation reveals whether the current wave is attracting participation (volume).
Normalization (Optional)
Volume can be normalized by the ATR (Average True Range) to account for volatility differences across symbols and timeframes. This makes comparisons more meaningful.
Strength Calculation
Volume strength is calculated by comparing current wave volume to the maximum over a recent period (default: 50 bars), and applying a pow() function for expressive scaling. This emphasizes high-effort waves while de-emphasizing noise.
🔶 USAGE
A new wave starts when the selected MA (SMA, EMA, WMA, HMA) changes direction.
Read the Strength of the Current Wave
🟩 — strong up
🟧 — weak up
🟪 — weak down
🟥 — strong down
Look for these setups
📉 Strong down wave 🟥 followed by weak up wave 🟧 — possible lower high, selling may resume.
📈 Strong up wave 🟩 followed by weak down wave 🟪 — possible bullish absorption, look for long setups.
Wave is long, but volume fades (bars shrink) — trend may be slowing, consider tightening stops or avoiding late entries.
Trend is increasing, volumes are growing — potential entry points.
Use Background Strength for Context
🟩 — bright green — strong bullish
🟥 — bright red — strong bearish
Any dim or translucent color — no clear trend
What NOT to do
Don’t enter blindly on volume spikes — check direction and trend background first.
Don’t treat every strong bar as a signal — look for sequences and transitions, not isolated bars.
Ideal Use Cases
Confirming trend strength before entry.
Avoiding fakeouts in low-volume waves.
Spotting transitions in buyer/seller dominance.
Reading market participation in real time.
SJ WaveTrendWaveTrend Indicator – Full English Brief for TradingView
Description:
The WaveTrend Oscillator (WT) is a momentum-based indicator originally developed by LazyBear, designed to identify overbought and oversold market conditions with high precision. It is conceptually similar to the RSI and Stochastic Oscillator but uses a wave-based mathematical approach to detect turning points in price action earlier and more smoothly.
⸻
🔍 How It Works
WaveTrend analyzes the difference between price and its moving average (typically the exponential moving average of the Typical Price).
It then applies multiple layers of smoothing to filter out noise and produce two oscillating lines — WT1 (fast) and WT2 (slow).
The crossing points between WT1 and WT2 are used to identify momentum shifts:
• When WT1 crosses above WT2 from below the oversold zone → Bullish signal
• When WT1 crosses below WT2 from above the overbought zone → Bearish signal
⸻
⚙️ Core Formula Concept
The WaveTrend calculation typically follows this process:
1. Compute the Typical Price (TP) = (High + Low + Close) / 3
2. Calculate the Exponential Moving Average (EMA) of TP over a short length
3. Determine the Raw Wave (ESA) and De-trended Price Oscillator (DPO)
4. Apply double smoothing to produce the final WT1 and WT2 values
These smoothed waves behave like energy waves that expand and contract based on market volatility — hence the name WaveTrend.
⸻
📈 Interpretation
• Overbought Zone: WT values above +60 to +70
• Oversold Zone: WT values below -60 to -70
• Crossovers: WT1 crossing WT2 signals a potential trend reversal
• Divergence: When price makes a new high/low but WT does not, it signals momentum weakening
⸻
🧠 Trading Insights
• Best used on higher timeframes (H1 and above) for trend confirmation, and on lower timeframes (M15–M30) for precise entries.
• Combine with ADX, EMA Cloud, or Volume Filters to confirm real momentum shifts and avoid false signals.
• You can highlight WT Diff (WT1 - WT2) to visualize momentum expansion and contraction; large positive or negative differences often precede strong reversals.
Wave Conflict DetectorWave Conflict Detector
Wave Conflict Detector: Identifying Pivot Conditions Through Wave Interference Analysis
Wave Conflict Detector applies wave interference principles from physics to dual-EMA analysis, identifying potential pivot conditions by measuring phase relationships and amplitude states between two moving average waves. Unlike traditional EMA crossover systems that signal on wave intersection, this indicator measures the directional alignment (phase) and interaction strength (interference amplitude) between wave states to identify conditions where wave mechanics suggest potential reversal zones.
The indicator combines two analytical components: velocity-based phase difference calculation that measures whether waves are moving in the same or opposite directions, and normalized interference amplitude that quantifies the degree of wave reinforcement or cancellation. This creates a regime-classification system with visual feedback showing when waves are aligned (constructive state) versus opposed (destructive state).
What Makes This Approach Different
Phase Relationship Measurement
The core analytical method is extracting phase alignment from wave velocities rather than simply measuring EMA separation. The system calculates the first derivative (bar-to-bar change) of each EMA, creating velocity measurements: v₁ = ψ₁ - ψ₁ and v₂ = ψ₂ - ψ₂ . These velocities are combined through normalized correlation: Φ = (v₁ × v₂) / |v|², producing an alignment value ranging from -1 (perfect opposition) to +1 (perfect alignment).
This alignment value is smoothed using EMA and converted to angular degrees: Δφ = (1 - Φ) × 90°, creating a phase difference measurement from 0° to 180°. This quantifies how much the waves are "fighting" each other directionally, independent of their separation distance. Two EMAs can be far apart yet moving in harmony (low phase difference), or close together yet moving in opposition (high phase difference).
This directional correlation approach differs from standard dual-EMA analysis by focusing on velocity alignment rather than positional crossovers.
Interference Amplitude Calculation
The interference formula implements wave superposition principles: I = (|ψ₁ + ψ₂|² - |ψ₁ - ψ₂|²) × Gain, which mathematically simplifies to I = 4 × ψ₁ × ψ₂ × Gain. This measures the product of both waves—when both are positive and large, interference is maximally constructive; when they have opposite signs or differing magnitudes, interference weakens.
The raw interference value is then normalized using adaptive statistical bounds calculated over a rolling window (default 100 bars). The system computes mean (μ) and standard deviation (σ) of raw interference, then applies bounds of μ ± 2σ, and normalizes to a 0-1 range. This creates a scale-invariant measurement that adapts automatically to different instruments and volatility regimes without requiring manual recalibration.
The combination of phase measurement and normalized amplitude creates a two-dimensional state space for classifying market conditions.
Dual-Mode Detection Architecture
The system offers two detection approaches that can be selected based on market conditions:
Interference Mode: Detects pivot conditions when normalized interference amplitude forms local peaks or troughs (current bar is higher/lower than both adjacent bars) AND exceeds the configured threshold. This identifies extremes in wave interaction strength.
Phase Mode: Detects pivot conditions when phase alignment reverses (crosses from positive to negative or vice versa) AND absolute phase difference exceeds the threshold. This identifies directional relationship changes between waves.
Both modes require price structure confirmation (traditional pivot high/low patterns) and minimum bar spacing to prevent over-signaling. This architecture allows traders to match detection sensitivity to market character—interference mode for amplitude-driven markets, phase mode for directional trend shifts.
Multi-Layer Visual System
The visualization approach uses hierarchical layers to display wave state information:
Foundation Layer: The two EMA waves (ψ₁ and ψ₂) plotted directly on the price chart, showing the underlying wave states being analyzed.
Background Layer: Color-coded zones showing regime state—green tint when phase alignment is positive (constructive interference), red tint when phase alignment is negative below -0.3 (destructive interference).
Dynamic Ribbon: A band centered on the wave average with width proportional to |ψ₁ - ψ₂| × (0.5 + interference_norm). This creates an adaptive channel that expands with interference strength and contracts during low-energy states.
Phase Field: Multi-frequency harmonic oscillations generated using three phase accumulators driven by interference amplitude, phase alignment, and accumulated phase rotation. Multiple sine-wave layers create visual texture that becomes erratic during wave conflict conditions and smooth during aligned states.
Particle System: Floating symbols whose density is proportional to interference amplitude, creating a visual intensity indicator.
Each visual component displays non-redundant information about the wave state system.
Core Calculation Methodology
Wave State Generation
Two exponential moving averages are calculated using configurable lengths (default 8 and 21 bars):
- ψ₁ = EMA(close, fastLen) — fast wave component
- ψ₂ = EMA(close, slowLen) — slow wave component
These serve as the base wave functions for all subsequent analysis.
Velocity Extraction
First derivatives are computed as simple bar-to-bar differences:
- psi1_velocity = ψ₁ - ψ₁
- psi2_velocity = ψ₂ - ψ₂
These represent the "motion" of each wave through price-time space.
Phase Alignment Calculation
The velocity product and magnitude are calculated:
- velocity_product = v₁ × v₂
- velocity_magnitude = √(v₁² + v₂²)
Phase alignment is computed as:
- phase_alignment = velocity_product / (velocity_magnitude²)
This is smoothed using EMA of configurable length (default 5) and converted to degrees:
- phase_degrees = (1 - phase_alignment_smooth) × 90
Interference Amplitude Processing
Raw interference is calculated:
- interference_raw = (constructive_amplitude - destructive_amplitude) × gain
- where constructive_amplitude = (ψ₁ + ψ₂)²
- and destructive_amplitude = (ψ₁ - ψ₂)²
Statistical normalization is applied:
- interference_mean = SMA(interference_raw, normalizationLen)
- interference_std = StdDev(interference_raw, normalizationLen)
- upper_bound = mean + 2 × std
- lower_bound = mean - 2 × std
- interference_norm = (interference_raw - lower_bound) / (upper_bound - lower_bound), clamped to
State Classification
Three regime states are identified:
- Constructive: phase_alignment_smooth > 0 (waves moving in same direction)
- Destructive: phase_alignment_smooth < -0.3 (waves moving in opposite directions)
- Neutral: phase_alignment between -0.3 and 0 (weak directional correlation)
Pivot Detection Logic
In Interference Mode:
- High pivots: interference_norm > interference_norm AND interference_norm > interference_norm AND interference_norm > threshold AND price forms pivot high AND spacing requirement met
- Low pivots: interference_norm shows local trough using opposite conditions
In Phase Mode:
- Pivots: phase alignment reverses sign AND absolute phase_degrees > threshold AND price forms pivot high/low AND spacing requirement met
All conditions must be true for a signal to generate.
Dashboard Metrics System
The dashboard displays real-time calculations:
- I (Interference): Normalized amplitude shown as bar gauge and percentage
- Δφ (Phase): Phase difference shown as bar gauge and degrees
- ψ₁ and ψ₂: Current wave values in price units
- Wave Separation: |ψ₁ - ψ₂| with directional indicator
- STATE: Current regime classification (CONSTRUCTIVE/DESTRUCTIVE/NEUTRAL)
- PIVOT Probability: Composite score calculated as interference_norm × (phase_degrees/180) × 100
The interference matrix shows historical heatmap data across four metrics (interference amplitude, phase difference, constructive flags, destructive flags) over the configurable number of bars.
How to Use This Indicator
Initial Configuration
Apply the indicator to your chart with default settings. The fast wave length (default 8) should be adjusted to match short-term price swings for your instrument and timeframe. The slow wave length (default 21) should be 2-4 times the fast length to create adequate wave separation. Enable the dashboard (recommended position: top right) to monitor regime state and metrics in real-time.
Signal Interpretation
High Pivot Marker (▼ Red Triangle): Appears above price bars when a bearish pivot condition is detected. This indicates that price formed a swing high, the selected detection criteria were met (interference peak or phase reversal depending on mode), threshold requirements were satisfied, and the minimum spacing filter passed. This represents a potential reversal zone where wave mechanics suggest downward directional change conditions.
Low Pivot Marker (▲ Green Triangle): Appears below price bars when a bullish pivot condition is detected. This indicates that price formed a swing low and all detection criteria aligned. This represents a potential reversal zone where wave mechanics suggest upward directional change conditions.
Dashboard STATE Reading
The STATE field shows current wave relationship:
- "🟢 CONSTRUCTIVE": Waves are moving in the same direction (phase alignment positive). This suggests trend continuation conditions where waves are reinforcing each other.
- "🔴 DESTRUCTIVE": Waves are moving in opposite directions (phase alignment below -0.3). This suggests reversal-prone conditions where waves are conflicting.
- "🟡 NEUTRAL": Weak directional correlation between waves. This suggests ranging or transitional conditions.
Use STATE for regime awareness rather than specific entry signals.
Interference and Phase Metrics
Monitor the I (Interference) percentage:
- Above 70%: High amplitude state, significant wave interaction
- 40-70%: Moderate amplitude state
- Below 40%: Low amplitude state, weak interaction
Monitor the Δφ (Phase) degrees:
- Above 120°: Significant wave opposition (destructive conditions)
- 60-120°: Transitional phase relationship
- Below 60°: Wave alignment (constructive conditions)
The PIVOT probability metric combines both: high values (>70%) indicate conditions where both amplitude and phase suggest elevated pivot formation potential.
Trading Workflow Example
Step 1 - Regime Check: Observe dashboard STATE to understand current wave relationship. CONSTRUCTIVE states favor trend-following approaches, DESTRUCTIVE states suggest reversal-prone conditions.
Step 2 - Metric Monitoring: Watch I% and Δφ values. Rising interference with high phase difference indicates building wave conflict.
Step 3 - Visual Confirmation: Observe amplitude ribbon width (expanding = active state) and phase field texture (chaotic = conflict conditions, smooth = aligned conditions).
Step 4 - Signal Wait: Wait for confirmed pivot marker (▼ or ▲) rather than anticipating based on metrics alone. The marker indicates all detection criteria have aligned.
Step 5 - Entry Decision: Use pivot markers as potential reversal zones. Combine with other analysis methods such as support/resistance levels, volume confirmation, and higher timeframe bias for entry decisions.
Step 6 - Risk Management: Place stops beyond recent swing structure or ribbon edges. Monitor dashboard STATE—if it flips to CONSTRUCTIVE in trade direction, the reversal may be confirmed; if PIVOT% drops significantly, conditions may be weakening.
Step 7 - Exit Criteria: Consider exits when opposite pivot marker appears, STATE changes unfavorably, or standard technical targets are reached.
Parameter Optimization Guidelines
Fast Wave Length: Adjust to match short-term swing frequency. Shorter values (5-8) for active trading on lower timeframes, longer values (13-20) for swing trading on higher timeframes.
Slow Wave Length: Should maintain 2-4x ratio with fast length. Shorter values create more interference cycles, longer values create more stable baseline.
Phase Detection Length: Smoothing for phase alignment. Lower values (3-5) for responsive detection, higher values (8-12) for stable readings with less sensitivity.
Interference Gain: Amplification multiplier. Lower values (0.5-1.0) for conservative detection, higher values (1.5-2.5) for more sensitive detection.
Normalization Period: Rolling window for statistical bounds. Shorter periods (50-100) adapt quickly to volatility changes, longer periods (150-300) provide more stable normalization.
Interference Threshold: Minimum amplitude to trigger signals. Lower values (0.50-0.60) generate more signals, higher values (0.70-0.85) are more selective.
Phase Threshold: Minimum phase difference in degrees. Lower values (90-110) are more permissive, higher values (140-170) require stronger opposition.
Min Pivot Spacing: Bars between signals. Match to average swing duration on your timeframe—tighter spacing (3-8 bars) for scalping, wider spacing (15-30 bars) for swing trading.
Best Performance Conditions
This approach works better in markets with:
- Clear swing structure where EMA-based wave analysis is meaningful
- Sufficient volatility for wave separation to develop
- Periodic oscillation between trending and ranging states
- Liquid instruments where EMAs reflect true price flow
This approach may be less effective in:
- Extremely choppy conditions with no directional persistence
- Very low volatility environments where wave separation is minimal
- Gap-heavy instruments where price discontinuities disrupt wave continuity
- Parabolic moves where waves cannot keep pace with price velocity
The system adapts by reducing signal frequency in poor conditions—when interference stays below threshold or phase alignment remains neutral, pivot markers will not appear.
Visual Performance Optimization
The phase field and particle systems are computationally intensive. If experiencing chart lag:
- Reduce Phase Field Layers from 5 to 2-3 (significant performance improvement)
- Lower Particle Density from 3 to 1 (reduces label creation overhead)
- Disable Phase Field entirely (removes most intensive calculations)
- Decrease Matrix History Bars to 15-20 (reduces table computation load)
The core wave analysis and pivot detection continue to function with all visual elements disabled.
Important Disclaimers
This indicator is an analytical tool that measures phase relationships and interference amplitude between two exponential moving averages. It identifies conditions where these wave mechanics suggest potential pivot zones based on historical price data analysis. It should not be used as a standalone trading system.
The phase and interference calculations are deterministic mathematical formulas applied to EMA values. These measurements describe current and historical wave relationships but do not predict future price movements. Past wave patterns and pivot markers do not guarantee future market behavior will follow similar patterns.
All trading involves risk. The pivot markers represent analytical conditions where wave mechanics align with specific thresholds, not certainty of directional change. Use appropriate risk management, position sizing, and combine with additional confirmation methods such as support/resistance analysis, volume patterns, and multi-timeframe alignment. No indicator can eliminate false signals or guarantee profitable trades.
The spacing filter and threshold requirements are designed to reduce noise and over-signaling, but market conditions can change rapidly and render any analytical signal invalid. Always use stop losses and never risk capital you cannot afford to lose.
Technical Implementation Notes
All calculations execute on closed bars only—there is no repainting of signals or values. The normalization system requires approximately 100 bars of historical data to establish stable statistical bounds; values in the first 50-100 bars may be unstable as the rolling statistics converge.
Phase field arrays are fixed-size based on the complexity setting. Particle labels are capped at 80 total to prevent excessive memory usage. Dashboard and matrix tables update only on the last bar to minimize computational overhead. Particle generation is throttled to every 2 bars for performance. Phase accumulators use modulo arithmetic (% 2π) to prevent numerical overflow during extended operation.
The indicator has been tested across multiple timeframes (5-minute through daily) and multiple asset classes (forex, stocks, crypto, indices). It functions identically across all instruments due to the adaptive normalization approach.
Elliott Wave - OscillatorWaves3: Indicated in RED Line(Upwards) and Green Line(Downwards)
- Detects wave greater than SMA
Waves4: Maximum height indicated in yellow Line
- Detects when wave greater than SMA (Wave 3 or 5) approaches wave 4 regression point
Waves5: Indicated in White Line
- Detects divergence in oscilator and price, meaning end of trend
Appreciate any suggestions, collaboration, comments or ideas.
Detects Waves 3 , 4 and 5
Alerts for Waves 3, 4 and 5(red, green and white)
WaveTrend Dynamic (Lazy Bear Style)█ OVERVIEW
The WaveTrend Dynamic indicator (in the style of Lazy Bear) is an advanced tool based on the Exponential Smoothing Average (ESA), which adapts to the volatility and price of a financial instrument. It is more flexible than the classic WaveTrend but shares a similar concept of bands around a main oscillator line.
The indicator uses dynamic bands calculated as distances from the ESA, with their width adjustable via the "level" parameter. This allows it to be tailored to various markets, timeframes, and volatility conditions, making it easier to identify trends, reversal points, and buy/sell signals.
█ CONCEPTS
The WaveTrend Dynamic combines oscillator functions with trend analysis. Below, we explain the key components in a simple way, understandable even for beginner users.
Core Calculations
The indicator relies on the adaptive ESA and a few straightforward steps:
1 — ESA (Adaptive Average): Calculated as a smoothed average of the price (from high, low, and close, or HLC3) using the ESA Length parameter (default: 10). This number determines how many past candles are considered in the calculation. The ESA quickly responds to price changes, helping to track trends.
2 — Deviation (D): Measures how much the price deviates from the ESA, factoring in market volatility. This allows the indicator to adapt to different instruments.
3 — Price Distance Indicator (CI): Shows how far the price is from the ESA relative to market volatility. This forms the basis for the main indicator line, reacting to price movements.
4 — WT1 (WaveTrend 1): The main line, smoothing the Price Distance Indicator (CI) with the Average Length parameter (default: 21). It reflects the direction of price movement and momentum.
5 — WT2 (WaveTrend 2): A signal line that further smooths WT1 (with a period of 4). It helps confirm signals through crossovers with WT1.
6 — Bands (UpperBand and LowerBand): These form a dynamic channel around the ESA. Their width depends on the level parameter (default: 100). Wider bands result in fewer but more reliable signals. In the original WaveTrend, the oscillator bands use lower values, such as 50 or 60. To achieve classic oscillator signals (more frequent WT1/WT2 crossovers outside the bands), set the level to 50–60.
Trend Identification
The indicator identifies two types of trends:
• Major Trend: Determined by the position of WT1 relative to the ESA. When WT1 is above the ESA, it indicates a bullish trend. When below, it signals a bearish trend. Line and fill colors reflect this trend.
• Mini-Trend: Based on WT1 and WT2 crossovers. When the lines cross, they change to the same color, signaling short-term changes or reversal points. This is ideal for quick trading decisions.
Visuals and Effects
• WT1 and WT2 Lines: Scaled to price and displayed on the price chart for easier analysis.
• Fills: Between the bands (UpperBand/LowerBand) and between WT1/WT2, with a "wave" effect that adjusts transparency based on the trend (green for bullish, red for bearish).
• Signals: Three types—return-to-band, WT1/WT2 crossovers outside the bands, and crossovers inside the bands. Signals are displayed as triangles with different colors for buy and sell.
█ FEATURES
Detailed features of the indicator, aligned with the order of settings in the script:
• Basic Parameters: ESA Length — controls ESA smoothing; Average Length — affects WT1 responsiveness; level (WT Level) — adjusts band width for signal filtering.
• Display Elements: Options to show/hide ESA, bands, WT1/WT2; customizable colors for lines, fills, and the wave effect.
• Signals: Three signal groups (return-to-band, crossovers outside bands, crossovers inside bands) with display and color customization options.
█ HOW TO USE
1 — Add the indicator to your TradingView chart and adjust parameters: — Increase ESA Length and Average Length for low-volatility markets (e.g., stocks), or decrease for cryptocurrencies or forex. — Set level to 50–60 for classic WaveTrend signals with WT1/WT2 crossovers outside bands. The default value of 100 creates wider bands and fewer signals.
2 — Analyze trends: — Major trend (WT1 vs. ESA) shows the overall market direction. — Mini-trends (WT1/WT2 crossovers) help time short-term entries.
3 — Use signals: — Return-to-band: Buy at the lower band, sell at the upper band (mean-reversion). — Crossovers outside bands: Indicate strong momentum (with a lower level, e.g., 50). — Crossovers inside bands: Signal weaker trend changes.
4 — Combine with other tools: Use with volume, RSI, or support/resistance for better decisions. Test on historical data to optimize settings.
Ichimoku PourSamadi Signal [TradingFinder] KijunSen Magic Number🔵 Introduction
The Ichimoku Kinko Hyo system is one of the most comprehensive market analysis tools ever created. Developed by Goichi Hosoda, a Japanese journalist in the 1930s, its purpose was to allow traders to recognize the balance between price, time, and momentum at a single glance. (In Japanese, Ichimoku literally means “one look.”)
At the core of the system lie five key components: Tenkan-sen (Conversion Line), Kijun-sen (Baseline), Chikou Span (Lagging Line), and the two leading spans, Senkou Span A and Senkou Span B, which together form the well-known Kumo or cloud representing both temporal structure and equilibrium zones in the market.
Although Ichimoku is commonly used to identify trends and support/resistance levels, a deeper layer of time philosophy exists within it. Ichimoku was not designed solely for price analysis but equally for time analysis.
In the classical model, the numerical cycles 9, 26, 52 reflect the natural rhythm of the market originally based on the Tokyo Stock Exchange’s trading schedule in the 1930s.
These values repeat across the system’s calculations, forming the foundation of Ichimoku’s time symmetry where price and time ultimately seek equilibrium.
In recent years, modern analysts have explored new approaches to extract time-based turning points from Ichimoku’s structure. One such approach is the analysis of flat segments on the Kijun-sen and Senkou B lines.
Whenever one of these lines remains flat for a period, it signals temporary balance between buyers and sellers; when the flat breaks, the market exits equilibrium and a new cycle begins.
This indicator is built precisely upon that philosophy. Following the timing methodology introduced by M.A. Poursamadi, the focus shifts away from price signals and line crossovers toward identifying flat periods on Kijun-sen (period 52) as time anchors.
From the first candle that changes the line’s slope, the tool begins a temporal count using a fixed sequence of key numbers: 5, 9, 13, 17, 26, 35, 43, 52, 63, 72, 81, 90.
Derived from both classical Ichimoku cycles and empirical testing, these numbers mark potential timing nodes where a market wave may end, a correction may begin, or a new leg may form.
Thus, this method serves not merely as another Ichimoku tool but as a temporal metronome for market structure a way to visualize moments when the market is ready to change rhythm, often before candles reveal it.
🔵 How to Use
The Kijun Timing BoX is built entirely on Ichimoku’s concept of time analysis.
Its core idea is that within every flat segment of the Kijun-sen, the market enters a temporary balance between opposing forces.
When that flat breaks, a new time cycle begins. From that first breakout candle, the indicator starts counting forward through the predefined time sequence(5, 9, 13, 17, 26, 35, 43, 52, 63, 72, 81, 90).
This counting framework creates a temporal map of market behavior, where each number represents an area where meaningful price fluctuations often occur.
A “meaningful fluctuation” does not necessarily imply reversal or continuation; rather, it marks a moment when the market’s internal energy balance shifts, typically visible as noticeable reactions on lower timeframes.
🟣 Identifying the Anchor Point
The first step is recognizing a valid flat zone on the Kijun-sen.
When this line remains flat for several candles and then changes slope, the indicator marks that bar as the Anchor, initiating the time count.
From that point onward, vertical gray lines appear at each interval in the key-number sequence, visualizing the time nodes ahead.
🟣 Reading the Timing Lines
Each numbered line represents a timing node a temporal point where a change in price rhythm is statistically more likely to occur.
At these nodes, the market may :
Enter a consolidation or minor correction phase.
Develop range-bound movement.
Or simply alter the speed and intensity of its move.
These behaviors do not imply a specific direction; they only highlight zones where time-based activity tends to cluster, giving traders a clearer view of cyclical rhythm.
🟣 Applying Time Analysis
The indicator’s primary use is to observe temporal order, not to predict price direction.
By tracking the distance between Anchors and the reactions that appear near major timing lines, traders can empirically identify each market’s characteristic rhythm—its own time DNA.
For example, one asset may consistently show significant fluctuations around the 13- and 26-bar marks,while another might react closer to 9 or 52. Recognizing such patterns helps traders understand how long typical cycles last before new phases of volatility emerge.
🟣 Combining with Other Tools
The indicator does not generate buy/sell signals on its own.
Its best use is in combination with price- or structure-based methods, to see whether meaningful price reactions occur around the same timing nodes.
In practice, it helps distinguish structured time-based fluctuations from random, noise-driven moves an insight often overlooked in conventional market analysis.
🔵 Settings
🟣 Logical Settings
KijunSen Period : Defines the baseline period used for timing analysis. Default = 52. It is the main line for detecting flats and generating time anchors.
Flat Event Filter : Controls how flat segments are validated before triggering a new timing event.
All : Every flat triggers a new Timing Box.
Automatic : Only flats longer than the historical average are used (recommended).
Custom : User manually defines the minimum flat length via Custom Count.
Update Timing Analysis BoX Per Event : If enabled, a new Timing Box is drawn each time a new flat event occurs. If disabled, the box completes its 90-bar window before refreshing.
🟣 Ichimoku Settings
TenkanSen Period : Defines the period for the Conversion Line (Tenkan-sen). Default = 9.
KijunSen Period : Sets the standard Ichimoku baseline (not the timing line). Default = 26.
Span B Period : Defines the period for Senkou Span B, the slower cloud boundary. Default = 52.
Shift Lines : Offsets cloud projection into the future. Default = 26.
🟣 Display Settings
Users can show or hide all Ichimoku lines Tenkan-sen, Kijun-sen, Chikou Span, Span A, and Span B as well as the Ichimoku Cloud.
They can also customize the color of each element to match personal chart preferences and improve visibility.
🔵 Conclusion
This analytical approach transforms Ichimoku’s time philosophy into a visual and measurable framework. A flat Kijun-sen represents a moment of market equilibrium; when its slope shifts, a new temporal cycle begins.
The purpose is not to forecast price direction but to highlight periods when meaningful fluctuations are more likely to develop.
Through this perspective, traders can observe the hidden rhythm of market time and expand their analysis beyond price into a broader time-cycle dimension.
Ultimately, the method revives Ichimoku’s original principle: the market can only be truly understood through the simultaneous harmony of price, time, and balance.
WaveTrend Oscillator PlusThe WaveTrend based on “Enhanced WaveTrend” of EliCobra. The WaveTrend Oscillator is a popular technical analysis tool used to identify overbought and oversold conditions in the market and generate trading signals. This indicator introduces additional features for improved analysis and comparison across assets.
WaveTrend:
The original WaveTrend indicator calculates two lines based on exponential moving averages and their relationship to the asset's price. The first line measures the distance between the asset's price and its EMA, while the second line smooths the first line over a specific period. The result is divided by 0.015 multiplied by the smoothed difference ('d' for reference). The indicator aims to identify overbought and oversold conditions by analyzing the relationship between the two lines.
In the original formula, the rudimentary estimation factor 0.015 times 'd' fails to accomodate for approximately a quarter of the data, preventing the indicator from reaching the traditional stationary levels of +-100. This limitation renders the indicator quantitatively biased, as it relies on the user's subjective adjustment of the levels. The enhanced version replaces this factor with the standard deviation of the asset's price, resulting in improved estimation accuracy and provides a more dynamic and robust outcome, we thereafter multiply the result by 100 to achieve a more traditional oscillation.
Enhancements and Features:
Dynamic Estimation: The original indicator uses an arbitrary estimation factor, while the enhanced version replaces it with the standard deviation of the asset's price. This modification provides a more dynamic and accurate estimation, adapting to the specific price characteristics of each asset.
Stationary Support and Resistance Levels: The enhanced version provides stationary key support and resistance levels that range from -150 to 150. These levels are determined based on the analysis of the indicator's data and encompass more than 95% of the indicator's values. These levels offer important reference points for traders to identify potential price reversals or significant price movements.
Comparison Across Assets: The enhanced version allows for better comparison and analysis across different assets. By incorporating the standard deviation of the asset's price, the indicator provides a more consistent and comparable interpretation of the market conditions across multiple assets.
Z-Score Analysis:
The Z-Score is a statistical measurement that quantifies how far a particular data point deviates from the mean in terms of standard deviations. In the enhanced version, the calculation involves determining the basis (mean) and deviation (standard deviation) of the asset's price to calculate its Z-Score, thereafter applying a smoothing technique to generate the final WaveTrend value.
Utility:
The offers traders and investors valuable insights into overbought and oversold conditions in the market. By analyzing the indicator's values and referencing the stationary support and resistance levels, traders can identify potential trend reversals, evaluate market strength, and make better informed analysis.
The following indicators were added:
⎆⎆ Squeeze Momentum Indicator
⎆⎆ Elliott Wave Oscillator
⎆⎆ Expert Trend Locator
WaveTrend Oscillator {Momentum} {DarkTheme} [NinjaDawgz]This is just a default set of settings i feel are best suited for Momentum trading and using Dark Theme.
it is the same code as the original
MFI is shown by default and the undertow wave is now a line for better visibility.
Custom Wave Trend Code used to spot, confirm and trade cyclical peaks and troughs.
Can be used in isolation but extremely powerful in conjunction with extra analysis, like Wave Theory.
WaveTrend Chart {Momentum} {DarkTheme} [NinjaDawgz]This is just a default set of settings i feel are best suited for Momentum trading and if you are using the Dark Theme.
it is the same code as the original
Custom Wave Trend Code used to spot, confirm and trade cyclical peaks and troughs.
Can be used in isolation but extremely powerful in conjunction with extra analysis, like Wave Theory.
Icon Descriptions:
Triangles (▼/▲): These are confirmations that the trend has changed. Trading in direction of the the trend is conservative but reliable and relatively profitable.
Pluses (+): These are points for re-entry and/or accumulating addition positions to trade the trend (Triangles above). If you missed the trend change, this is best place to get in.
Crosses (x): Picking the top and bottom is hard, like catching falling knife. This will show you possible tops/bottoms as they happen. Can be noisy, should not be used in isolation.
Diamonds (♦): NEW! Wish the trend confirmation (triangles) was quicker? This does
Works on any time frame, any security (Stocks, Forex, Crypto's, etc.)
Green for Long, Red for Short.
All icons can be used for Alerts!
New Alert (Alt + A) > Change Condition to WaveTrend_Chart > Choose from the list of icons.
WaveTrend Oscillator {Momentum} [NinjaDawgz]This is just a default set of settings i feel are best suited for Momentum trading.
it is the same code as the original
MFI is shown by default and the undertow wave is now a line for better visibility.
Custom Wave Trend Code used to spot, confirm and trade cyclical peaks and troughs.
Can be used in isolation but extremely powerful in conjunction with extra analysis, like Wave Theory.
Wave Trading HelperThis script can be helpful to find trend and EP, SL, TP.
I tested only LTF(Lower Time Frame) such as under 15 mimutes for very short term trading.
As you see this script came from MAs and i'd adjusted the lengths and sources.
Basical Usages.
There are several lines but you must remember that the border is support and resistant as other MAs.
- The upper border is resistant and the lower borader is support line.
Once you chacked the trends with waves.
- If it goes up then Up-trend, and vice versa.
- when the trend change, there is flip over the waves as I circled on above.
- To make an Entry Point and STOP LOSS
Once, if there is a Flip orver, then you should take a look at the lime colored line and that is the entry line.
The Lower Border is Stop Loss.
- Hold the Position
Once, the waves spread out then the Trend is accellating so, you should hold the position.
- To take a profit.
When another Flip over you can take a profit on the Enrty line.
or when the candle hits STOP LOSS LINE then the trade is over.
It is very easy and simple isn't it?
WaveTrend RBF What it does
WT-RBF extracts a “wave” of momentum by subtracting a fast Gaussian-weighted smoother from a slow one, then robust-normalizes that wave with a median/MAD proxy to produce a z-score (z). A short EMA of z forms the signal line. Optional dynamic thresholds use the MAD of z itself so overbought/oversold levels adapt to volatility regimes.
How it’s built:
Radial (Gaussian) smoothers
Causal, exponentially-decaying weights over the last radius bars using σ (sigma) to control spread.
fast = rbf_smooth(src, fastR, fastSig)
slow = rbf_smooth(src, slowR, slowSig)
wave = fast − slow (band-pass)
Robust normalization
A two-stage EMA approximates the median; MAD is estimated from EMA of absolute deviations and scaled by 1.4826 to be stdev-comparable.
z = (wave − center) / MAD
Thresholds
Dynamic OB/OS: ±2.5 × MAD(z) (or fixed levels when disabled)
Reading the indicator
Bull Cross: z crosses above sig → momentum turning up.
Bear Cross: z crosses below sig → momentum turning down.
Exits / Bias flips: zero-line crosses (below 0 → exit long bias; above 0 → exit short bias).
Overbought/Oversold: z > +thrOB or z < thrOS. With dynamics on, the bands widen/narrow with recent noise; with dynamics off, static guides at ±2 / ±2.5 are shown.
Core Inputs
Source: Price series to analyze.
Fast Radius / Fast Sigma (defaults 6 / 2.5): Shorter radius/smaller σ = snappier, higher-freq.
Slow Radius / Slow Sigma (defaults 14 / 5.0): Larger radius/σ = smoother, lower-freq baseline.
Normalization
Robust Z-Score Window (default 200): Lookback for median/MAD proxy (stability vs responsiveness).
Small ε for MAD: Floor to avoid division by zero.
Signal & Thresholds
Dynamic Thresholds (MAD-based) (on by default): Adaptive OB/OS; toggle off to use fixed guides.
Visuals
Shade OB/OS Regions: Background highlights when z is beyond thresholds.
Show Zero Line: Midline reference.
(“Plot Cross Markers” input is present for future use.)
Wavelet-Trend ML Integration [Alpha Extract]Alpha-Extract Volatility Quality Indicator
The Alpha-Extract Volatility Quality (AVQ) Indicator provides traders with deep insights into market volatility by measuring the directional strength of price movements. This sophisticated momentum-based tool helps identify overbought and oversold conditions, offering actionable buy and sell signals based on volatility trends and standard deviation bands.
🔶 CALCULATION
The indicator processes volatility quality data through a series of analytical steps:
Bar Range Calculation: Measures true range (TR) to capture price volatility.
Directional Weighting: Applies directional bias (positive for bullish candles, negative for bearish) to the true range.
VQI Computation: Uses an exponential moving average (EMA) of weighted volatility to derive the Volatility Quality Index (VQI).
Smoothing: Applies an additional EMA to smooth the VQI for clearer signals.
Normalization: Optionally normalizes VQI to a -100/+100 scale based on historical highs and lows.
Standard Deviation Bands: Calculates three upper and lower bands using standard deviation multipliers for volatility thresholds.
Signal Generation: Produces overbought/oversold signals when VQI reaches extreme levels (±200 in normalized mode).
Formula:
Bar Range = True Range (TR)
Weighted Volatility = Bar Range × (Close > Open ? 1 : Close < Open ? -1 : 0)
VQI Raw = EMA(Weighted Volatility, VQI Length)
VQI Smoothed = EMA(VQI Raw, Smoothing Length)
VQI Normalized = ((VQI Smoothed - Lowest VQI) / (Highest VQI - Lowest VQI) - 0.5) × 200
Upper Band N = VQI Smoothed + (StdDev(VQI Smoothed, VQI Length) × Multiplier N)
Lower Band N = VQI Smoothed - (StdDev(VQI Smoothed, VQI Length) × Multiplier N)
🔶 DETAILS
Visual Features:
VQI Plot: Displays VQI as a line or histogram (lime for positive, red for negative).
Standard Deviation Bands: Plots three upper and lower bands (teal for upper, grayscale for lower) to indicate volatility thresholds.
Reference Levels: Horizontal lines at 0 (neutral), +100, and -100 (in normalized mode) for context.
Zone Highlighting: Overbought (⋎ above bars) and oversold (⋏ below bars) signals for extreme VQI levels (±200 in normalized mode).
Candle Coloring: Optional candle overlay colored by VQI direction (lime for positive, red for negative).
Interpretation:
VQI ≥ 200 (Normalized): Overbought condition, strong sell signal.
VQI 100–200: High volatility, potential selling opportunity.
VQI 0–100: Neutral bullish momentum.
VQI 0 to -100: Neutral bearish momentum.
VQI -100 to -200: High volatility, strong bearish momentum.
VQI ≤ -200 (Normalized): Oversold condition, strong buy signal.
🔶 EXAMPLES
Overbought Signal Detection: When VQI exceeds 200 (normalized), the indicator flags potential market tops with a red ⋎ symbol.
Example: During strong uptrends, VQI reaching 200 has historically preceded corrections, allowing traders to secure profits.
Oversold Signal Detection: When VQI falls below -200 (normalized), a lime ⋏ symbol highlights potential buying opportunities.
Example: In bearish markets, VQI dropping below -200 has marked reversal points for profitable long entries.
Volatility Trend Tracking: The VQI plot and bands help traders visualize shifts in market momentum.
Example: A rising VQI crossing above zero with widening bands indicates strengthening bullish momentum, guiding traders to hold or enter long positions.
Dynamic Support/Resistance: Standard deviation bands act as dynamic volatility thresholds during price movements.
Example: Price reversals often occur near the third standard deviation bands, providing reliable entry/exit points during volatile periods.
🔶 SETTINGS
Customization Options:
VQI Length: Adjust the EMA period for VQI calculation (default: 14, range: 1–50).
Smoothing Length: Set the EMA period for smoothing (default: 5, range: 1–50).
Standard Deviation Multipliers: Customize multipliers for bands (defaults: 1.0, 2.0, 3.0).
Normalization: Toggle normalization to -100/+100 scale and adjust lookback period (default: 200, min: 50).
Display Style: Switch between line or histogram plot for VQI.
Candle Overlay: Enable/disable VQI-colored candles (lime for positive, red for negative).
The Alpha-Extract Volatility Quality Indicator empowers traders with a robust tool to navigate market volatility. By combining directional price range analysis with smoothed volatility metrics, it identifies overbought and oversold conditions, offering clear buy and sell signals. The customizable standard deviation bands and optional normalization provide precise context for market conditions, enabling traders to make informed decisions across various market cycles.
Parsifal.Swing.CompositeThe Parsifal.Swing.Composite indicator is a module within the Parsifal Swing Suite, which includes a set of swing indicators such as:
• Parsifal Swing TrendScore
• Parsifal Swing Composite
• Parsifal Swing RSI
• Parsifal Swing Flow
Each module serves as an indicator facilitating judgment of the current swing state in the underlying market.
________________________________________
Background
Market movements typically follow a time-varying trend channel within which prices oscillate. These oscillations—or swings—within the trend are inherently tradable.
They can be approached:
• One-sidedly, aligning with the trend (generally safer), or
• Two-sidedly, aiming to profit from mean reversions as well.
Note: Mean reversions in strong trends often manifest as sideways consolidations, making one-sided trades more stable.
________________________________________
The Parsifal Swing Suite
The modules aim to provide additional insights into the swing state within a trend and offer various trigger points to assist with entry decisions.
All modules in the suite act as weak oscillators, meaning they fluctuate within a range but are not bounded like true oscillators (e.g., RSI, which is constrained between 0% and 100%).
________________________________________
The Parsifal.Swing.Composite – Specifics
This module consolidates multiple insights into price swing behavior, synthesizing them into an indicator reflecting the current swing state.
It employs layered bagging and smoothing operations based on standard price inputs (OHLC) and classical technical indicators. The module integrates several slightly different sub-modules.
Process overview:
1. Per candle/bin, sub-modules collect directional signals (up/down), with each signal casting a vote.
2. These votes are aggregated via majority counting (bagging) into a single bin vote.
3. Bin votes are then smoothed, typically with short-term EMAs, to create a sub-module vote.
4. These sub-module votes are aggregated and smoothed again to generate the final module vote.
The final vote is a score indicating the module’s assessment of the current swing state. While it fluctuates in a range, it's not a true oscillator, as most inputs are normalized via Z-scores (value divided by standard deviation over a period).
• Historically high or low values correspond to high or low quantiles, suggesting potential overbought or oversold conditions.
• The chart displays a fast (orange) and slow (white) curve against a solid background state.
• Extreme values followed by curve reversals may signal upcoming mean-reversions.
Background Value:
• Value > 0: shaded green → bullish mode
• Value < 0: shaded red → bearish mode
• The absolute value indicates confidence in the mode.
________________________________________
How to Use the Parsifal.Swing.Composite
Several change points in the indicator serve as potential entry triggers:
• Fast Trigger: change in slope of the fast curve
• Trigger: fast line crossing the slow line or change in the slow curve’s slope
• Slow Trigger: change in sign of the background value
These are illustrated in the introductory chart.
Additionally, market highs and lows aligned with swing values may act as pivot points, support, or resistance levels for evolving price processes.
________________________________________
As always, supplement this indicator with other tools and market information. While it provides valuable insights and potential entry points, it does not predict future prices. It reflects recent tendencies and should be used judiciously.
________________________________________
Extensions
All modules in the Parsifal Swing Suite are simple yet adaptable, whether used individually or in combination.
Customization options:
• Weights in EMAs for smoothing are adjustable
• Bin vote aggregation (currently via sum-of-experts) can be modified
• Alternative weighting schemes can be tested
Advanced options:
• Bagging weights may be historical, informational, or relevance-based
• Selection algorithms (e.g., ID3, C4.5, CAT) could replace the current bagging approach
• EMAs may be generalized into expectations relative to relevance-based probability
• Negative weights (akin to wavelet transforms) can be incorporated
WaveTrend Matrix (1m-1w) – Custom ThresholdsA visual control panel for momentum exhaustion across ten key time-frames.
—
🧬 DNA
This is a fork of LazyBear’s original WaveTrend Oscillator .
The oscillator logic is 100 % intact; I simply stream the values into a compact table so that day- and swing-traders can see the “bigger picture” at a glance.
📈 What does it do?
Calculates WaveTrend on ten granularities: 1m, 3m, 5m, 15m, 30m, 1h, 2h, 4h, 1d, 1w.
Displays the current oscillator print in a color-coded matrix.
• Red = overbought (≥ high threshold)
• Green = oversold (≤ low threshold)
• Gray = neutral / in-range
All thresholds are user-adjustable.
Built on Pine v5, zero repainting, works on any symbol.
🛠 Parameters
Channel Length – WT “n1” (default 10)
Average Length – WT “n2” (default 21)
Red from – overbought cut-off (default +60)
Green under – oversold cut-off (default –60)
🚀 How to use it
1. Apply the indicator to your chart – no extra setup required.
2. Read the matrix top-down before every entry:
• Multiple deep-green rows → market broadly oversold → watch for longs.
• Multiple deep-red rows → market broadly overbought → watch for shorts or stay flat.
3. Combine with your trend filter (EMA-stack, VWAP, structure) to avoid counter-trend trades.
NEoWave Chart Cash Data The NEoWave Chart Cash Data indicator is an efficient tool for generating wave charts or cash data based on the NeoWave method, benefiting not only NeoWave analysts but also Elliott Wave practitioners. This indicator produces cash data with exceptional precision.
Developed by Glenn Neely, NeoWave is considered a more complete, scientific, and innovative iteration of the Elliott Wave theory. This method relies on a specialized chart known as a "wave chart" or "cash data," which, when drawn manually by recording the highest and lowest prices in their order of occurrence, is a complex and time-consuming process. However, this indicator automatically and in real-time identifies the highest and lowest prices for any symbol and time frame, plotting them in sequence. For instance, in a daily time frame, it separates each month's data and prepares a "monthly cash data chart" for analysis using the NeoWave method.
Fully compatible with all account types, this tool enables the creation of cash data across various time frames (from minutes to years) and customizable scales. Its standout features include real-time updates, watermarking capabilities, display of useful data in tables, detection of suspicious monowaves (where the highest and lowest prices occur within the same candlestick), simultaneous display of two cash data charts with different time frames, and the ability to view cash data for any desired time period.
CASH DATA TIMEFRAMES
The core feature of this indicator is CASH DATA TIMEFRAMES, which generates and displays Cash Data based on your base timeframe. Here’s how it works:
.1 Minute ("1"): Cash Data: 5, 10, 15, 30, 60, 120, 180 minutes
.3 Minutes ("3"): Cash Data: 30, 60, 120, 180, 240 minutes
.5 Minutes ("5"): Cash Data: 30, 60, 120, 180, 240 minutes, 1 day (1D)
.15 Minutes ("15"): Cash Data: 120, 180, 240 minutes, 1 day (1D), 2 days (2D), 3 days (3D)
.30 Minutes ("30"): Cash Data: 180, 240 minutes, 1 day (1D), 2 days (2D), 3 days (3D), 1 week (1W)
.1 Hour ("60"): Cash Data: 1 day (1D), 2 days (2D), 3 days (3D), 1 week (1W), 2 weeks (2W)
.2 Hours ("120"): Cash Data: 1 day (1D), 2 days (2D), 3 days (3D), 1 week (1W), 2 weeks (2W), 1 month (1M)
.3 Hours ("180"): Cash Data: 1 day (1D), 2 days (2D), 3 days (3D), 1 week (1W), 2 weeks (2W), 1 month (1M)
.4 Hours ("240"): Cash Data: 2 days (2D), 3 days (3D), 1 week (1W), 2 weeks (2W), 1 month (1M), 2 months (2M)
.Daily ("D"): Cash Data: 1 week (1W), 2 weeks (2W), 1 month (1M), 2 months (2M), 3 months (3M), 6 months (6M), 12 months (12M)
.Weekly ("W"): Cash Data: 2 months (2M), 3 months (3M), 6 months (6M)
.Monthly ("M"): Cash Data: 6 months (6M), 12 months (12M)
Suspicious monowaves
Suspicious monowaves, visible in the "Inputs" section under the label "Sus Monowaves," are highlighted in red upon detection. This occurs when the highest and lowest prices within a given time period appear in a single candlestick. As illustrated, suspicious monowaves are marked with red squares, and the candlestick indicated by a red arrow is the trigger for identifying these monowaves.
In such instances, our indicator automatically plots the monowaves with high precision. This feature is tailored for users seeking cash data of the utmost accuracy. Whenever these monowaves appear on the chart, it is recommended that users examine the suspicious monowaves in a lower time frame for further analysis.
Other Cash Data TF
One of the key features of this indicator is the "Other Cash Data TF" option, which, when enabled, allows you to create two cash data charts with different time frames within your base time frame. This feature becomes particularly useful when, for example, your base time frame is daily, and you’ve identified a pattern like a zigzag in the monthly cash data. To confirm this pattern, you need to examine the internal waves A and C to determine whether they are impulsive. By activating this option and setting "Other TF" to a weekly time frame, you can easily analyze the internal waves of your chosen wave without altering the base time frame.
When this option is activated, a column is added to the table, indicating that the "Base TF" is daily, "Cash Data TF" is monthly, and "Other Cash Data TF" is weekly (as shown in the image below).
Other features of the indicator include:
.A Table providing useful information such as the symbol, base time frame, cash data time frame (Cash Data TF), number of monowaves, and live price.
.Customizable options for the table (including color, size, and column removal), watermark, cash data lines, suspicious monowaves, and more.
.A Time Separator that divides the chart into equal periods.
.The ability to add a watermark.
Market Structures + ZigZag [TradingFinder] CHoCH/BOS - MSS/MSB🟣 Introduction
🔵 Market Structure
Grasping market structure entails examining market behavior. Essentially, market structure refers to the formation and progression of the market within its trends.
Market structures are generally fractal and nested, leading us to classify them into internal (minor) and external (major) structures. There are several definitions of market structure, with differing perspectives such as Smart Money and ICT offering their own interpretations.
🔵 Zig Zag
The Zigzag indicator is a lagging tool that identifies points on a price chart where significant changes occur compared to the previous wave. By connecting these points, it helps traders detect trends.
This indicator minimizes random price fluctuations, aiming to clarify the primary price trend.
Pivots are points on a price chart where the direction changes. Also known as reversal points, pivots form when supply and demand forces overpower one another.
There are various types of technical analysis pivots, which can be divided into two categories: minor pivots and major pivots, each with distinct significance in analysis.
Major Pivot : These pivots signify substantial changes in the chart's direction and occur at the end of trends. Analysts focusing on primary analysis prioritize major pivot points. In fact, most technical analysis tools are evaluated and based on major pivots.
Minor Pivot : These pivots highlight smaller, subsidiary points and directions, appearing at the end of corrections. Analysts who focus on minor pivots represent small trends. It's important to note that minor pivots are not suitable for use in primary technical tools.
Identifying Minor and Major Pivots :
Minor pivots are formed between two major pivots and do not break the opposing major pivot. (Internal Pivot)
Major pivots are those that either successfully break the opposing pivot or move beyond the previous pivot of the same type. (External Pivot)
🟣 How to Use
🔵 Identifying Break of Structure (BOS)
In a given trend, such as a downtrend, a Break of Structure occurs when the price drops below the previous low and forms a new low (LL). In an uptrend, a BOS (MSB) happens when the price rises and exceeds the last high.
To confirm a trend, at least one BOS is required. The break above or below the previous high or low must be validated by the closing of at least one candle beyond that level.
🔵 Identifying Change of Character (CHOCH)
Change of Character (CHOCH) is an essential concept in market structure analysis, indicating a trend change. In other words, a trend concludes with a CHOCH (MSS). For example, in a downtrend, the price declines with BOS.
While BOS highlights the trend's strength, a CHOCH occurs when the price rises and surpasses the last high, signaling a transition from a downtrend to an uptrend.
This does not imply immediately entering a buy trade; instead, it is prudent to wait for a BOS in the upward direction to confirm the uptrend.
Unlike BOS, confirming a CHOCH does not require a candle to close; simply breaking above or below the previous high or low with the candle's wick is sufficient. The following examples illustrate bearish and bullish CHOCH.
Terms :
Market Structure Shift = MSS
Market Structure Break = MSB
🔵 Zig Zag
Based on identifying pivots and drawing zigzag lines, you can have different uses of this indicator.
Including :
Identifying pivot types along with major and minor recognition.
Identifying internal and external breakouts.
Identifying support and resistance levels.
Identifying Elliott Waves.
Identifying classic patterns.
Identifying pivots with higher validity.
Identifying trends and range areas.
🟣 Settings
Pivot Period Market Structure and ZigZag Line: Using this input, you can determine the pivot period for identifying swings.
Through the settings, you can customize the display, visibility, and color of each line as desired.
WaveTrendnel Oscillator [UAlgo]🔶Description:
The WaveTrendnel Oscillator, is a technical analysis tool designed for traders to identify potential trend reversals and overbought/oversold conditions in the market. It combines the concepts of wave analysis and trend analysis to generate signals based on the current market conditions. This indicator aims to provide traders with insights into the strength and direction of the prevailing trend, facilitating better decision-making in trading strategies.
🔶Key Features:
Customizable Parameters: Users can customize various parameters including the source data, channel length, average length, and signal length according to their trading preferences and market conditions.
Signal Display: The indicator offers the option to display buy and sell signals on the chart, helping traders to visually identify potential entry and exit points.
Wave and Kernel Analysis: The WaveTrendnel Oscillator utilizes a rational quadratic kernel function, which applies a mathematical approach known as the kernel method. This method analyzes historical price data by assigning weights to each data point based on its proximity to the current period, providing a smoother and more accurate representation of market trends.
Overbought/Oversold Levels: Traders can define overbought and oversold levels using customizable threshold parameters, enabling them to identify potential reversal points in the market.
🔶Credit:
The WaveTrendnel Oscillator indicator is a modification of the original WaveTrend Oscillator developed by @LazyBear on TradingView.
🔶Disclaimer:
Use with Caution: This indicator is provided for educational and informational purposes only and should not be considered as financial advice. Users should exercise caution and perform their own analysis before making trading decisions based on the indicator's signals.
Not Financial Advice: The information provided by this indicator does not constitute financial advice, and the creator (UAlgo) shall not be held responsible for any trading losses incurred as a result of using this indicator.
Backtesting Recommended: Traders are encouraged to backtest the indicator thoroughly on historical data before using it in live trading to assess its performance and suitability for their trading strategies.
Risk Management: Trading involves inherent risks, and users should implement proper risk management strategies, including but not limited to stop-loss orders and position sizing, to mitigate potential losses.
No Guarantees: The accuracy and reliability of the indicator's signals cannot be guaranteed, as they are based on historical price data and past performance may not be indicative of future results.
DEMO - FxCanli ZigZagEN - You can spot current trend and lots of patterns with FxCanli ZigZag indicator EASLY
DEMO VERSION of FXCANLI ZIGZAG Indicator works on only GBPNZD and XRPUSDT charts
TR - FxCanli ZigZag indikatörü mevcut trendi ve birçok formasyonu KOLAYCA bulmanızda size yardımcı olacaktır.
FXCANLI ZIGZAG indikatörünün DEMO VERSİYONU sadece GBPNZD ve XRPUSDT grafiklerinde çalışır
EN - Market Structure (At the Current time frame you can choose different colors for UpTrend and DownTrend)
TR - Market Yapısı (Mevcut zaman diliminde, Yukarı Trend ve Aşağı trendin rengini seçebilirsiniz.)
Harmonic Patterns / Harmonik Formasyonları
Elliott Wave / Elliott Dalgaları
AB=CD Pattern / AB=CD Formasyonu
EN - By activating the lower timeframe from the settings, you can see the lower timeframe waves.
TR - Ayarlardan alt zaman dilimini aktif ederek, alt zaman dilimi dalgalarını görebilirsiniz.
EN - By activating the higher timeframe from the settings, you can see the higher timeframe waves.
TR - Ayarlardan üst zaman dilimini aktif ederek, üst zaman dilimi dalgalarını görebilirsiniz.
Wavechart v2 ##Wave Chart v2##
For analyzing Neo-wave theory
Plot the market's highs and lows in real-time order.
Then connect the highs and lows
with a diagonal line. Next, the last plot of one day (or bar) is connected with a straight line to the
first plot of the next day (or bar).
