Wavelets Suite
See what traditional indicators miss
Decompose price action into distinct timescales using mathematically rigorous wavelet transforms. Powered by VectorWave, the Wavelets Suite brings institutional-grade multi-resolution analysis to your trading, revealing structure that traditional indicators simply cannot see.
Learn how wavelet indicators improve trend and cycle analysis →
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5 Professional Studies
Wavelet Analysis
Multi-scale decomposition
View 7 independent frequency bands (D1-D7) simultaneously using the MODWT transform with multiple wavelet families including Daubechies, Symlets, Coiflets, and Haar.
- • Intelligent denoising with BayesShrink and Universal thresholding
- • Auto-window sizing based on wavelet mathematical properties
- • Identify which timescale is driving current price action
Wavelet Trend Ratio
Clear trending vs ranging detection with natural threshold
Know whether you're in a trend or range using a log-scaled ratio of trend energy to noise energy. Zero is the natural threshold — positive means trending, negative means ranging. No arbitrary settings needed.
- • Natural zero threshold separates trending from ranging regimes
- • Log scale provides consistent interpretation across instruments
- • Returns-based analysis eliminates price level bias
Parameters
- • Wavelet Family — Daubechies (db4), Symlet, Coiflet, or Haar
- • Decomposition Levels — Number of wavelet scales to analyze (default: 4)
- • Smoothing Period — EMA smoothing for log ratio (default: 5)
- • Strong Threshold — Log ratio for very strong trend (default: 1.0 ≈ 2.7x ratio)
- • Show Quality — Optional percentile line for relative comparison
Signal Logic
- TREND_STARTED — Ratio crosses above zero. Trend energy now exceeds noise energy.
- TREND_ENDED — Ratio crosses below zero. Noise energy now exceeds trend energy.
- STRONG_TREND — Ratio crosses above strong threshold (1.0). Very strong trending conditions.
- TREND_WEAKENING — Ratio falls below strong threshold from above. Strong trend deteriorating.
Interpretation
- • > 2.0 — Very strong trend (7x more trend than noise)
- • > 1.0 — Strong trend (2.7x ratio)
- • > 0 — Trending (trend energy dominates)
- • = 0 — Break-even (trend equals noise)
- • < 0 — Ranging (noise energy dominates)
Trading Applications
- • Trend Filter — Only enter trend trades when ratio > 0
- • High-Confidence Setups — Look for ratio > 1.0 for strong trends
- • Mean-Reversion — Favor mean-reversion when ratio < 0
- • Regime Detection — Zero line clearly separates market regimes
Wavelet Cycle Detector
Identify turning points before they're obvious
Detect potential cycle highs and lows using wavelet zero-crossings with multi-level confluence scoring. Combines D3 (8-16 bars), D4 (16-32 bars), and D5 (32-64 bars) for high-probability signals.
- • Temporal alignment — crossings within configurable window count as aligned
- • Cycle length estimation tracks average period between turning points
- • Signals: CYCLE_HIGH, CYCLE_LOW, STRONG_HIGH, STRONG_LOW
Wavelet ATR (H-WATR)
Smarter volatility for better stops
A hybrid ATR that blends baseline magnitude with regime variance. Adapts faster to volatility changes while remaining stable for position sizing. Three profiles: Balanced, Magnitude Focused, and Regime Focused.
- • Built-in Moving Average, Bollinger Bands, and Percentile context
- • Detect volatility compression before breakouts ("coiling")
- • Signals: VOLATILITY_RISING, VOLATILITY_FALLING, SPIKE, COLLAPSE, EXTREME_HIGH, EXTREME_LOW
Wavelet ATR Bands
Dynamic volatility channels on price
Volatility-based price bands using the same hybrid H-WATR algorithm. Upper and lower bands at configurable multiples of WATR provide visual support/resistance and stop placement guides.
- • Same three volatility profiles as Wavelet ATR
- • Band width adapts to market regime automatically
- • Price overlay — see volatility context directly on chart
Technical Highlights
Real-Time Performance
O(1) live bar updates using streaming MODWT technology. Sub-millisecond updates during live trading while traditional implementations recalculate the entire transform on every tick.
Mathematically Sound
Built on MODWT — a shift-invariant transform that maintains data length at each decomposition level. No downsampling means no information loss. Crossings align with actual price turns.
Signal Generation
All studies generate actionable signals for automated alerts. Crossover-based detection prevents signal spam. Full integration with MotiveWave's signal and alert system.
Professional Integration
Native MotiveWave integration with consistent settings interface across all studies. Exportable values for strategy backtesting. Configurable visual appearance.
Why Wavelets?
Traditional indicators treat all price movements equally. Wavelets decompose price into distinct frequency bands, letting you:
- • See structure at multiple timescales simultaneously — without changing chart timeframes
- • Separate signal from noise mathematically — not with arbitrary smoothing
- • Detect regime changes faster — wavelets adapt to non-stationary data
- • Avoid lag — MODWT is shift-invariant; crossings align with actual price turns
Wavelet Trend Ratio FAQ
How is this different from ADX?
ADX measures trend strength using smoothed directional movement over a single timeframe with significant lag. Wavelet Trend Ratio uses a log-scaled ratio of trend energy to noise energy with a natural threshold at zero — positive values indicate trending, negative values indicate ranging. This provides clearer regime identification without arbitrary threshold selection, plus returns-based calculation makes it immune to price level effects that can distort ADX readings.
What does the zero line mean?
Zero is the natural break-even point where trend energy equals noise energy (ratio = 1, log(1) = 0). Values above zero indicate trending conditions where directional movement dominates. Values below zero indicate ranging/choppy conditions where noise dominates. This eliminates the need for arbitrary threshold settings — the math provides the meaningful boundary.
Which wavelet family should I choose?
Daubechies (db4) is the default and works well for most markets due to its balance of smoothness and localization. Haar is fastest computationally and captures sharp transitions but is less smooth. Symlets provide near-symmetric filters if phase alignment is critical. Coiflets offer more vanishing moments for smoother approximations. Start with db4 and only change if you have specific requirements.
What do the values mean?
Values above 2.0 indicate very strong trends (about 7x more trend energy than noise). Values above 1.0 indicate strong trends (about 2.7x ratio). Values near zero are transitional. Values below -1.0 indicate strongly ranging/choppy conditions. The log scale compresses extreme values while preserving meaningful differences — a value of 2 is always interpretable as "strong trend" regardless of instrument or timeframe.
Can I use this for mean-reversion strategies?
Yes. Negative values indicate ranging conditions ideal for mean-reversion strategies. Use TREND_ENDED signals to identify when trending has stopped and conditions favor mean-reversion. Avoid mean-reversion entries when TREND_STARTED or STRONG_TREND signals appear. The zero line provides a clear regime boundary for strategy selection.