- Implemented the TRAMA (Trend Regularity Adaptive Moving Average) class with adaptive EMA logic.
- Added unit tests for TRAMA functionality, including constructor validation, basic calculations, state management, and robustness checks.
- Created validation tests to ensure consistency across different modes of operation (streaming, batch, and static calculations).
- Enhanced documentation for TRAMA, including performance profiles and quality metrics.
- Updated workspace configuration by removing unnecessary folder references.
- LTMA (Linear Trend Moving Average): Introduces a predictive moving average using dual cascaded EMAs for trend estimation.
- MCNMA (McNicholl EMA): Implements a zero-lag TEMA using a cascaded EMA structure for enhanced responsiveness.
- NLMA (Non-Lag Moving Average): Utilizes a damped cosine kernel to achieve reduced lag in moving averages.
- NMA (Natural Moving Average): Adapts smoothing based on volatility profiles using a square-root kernel.
- NYQMA (Nyquist Moving Average): Applies the Nyquist-Shannon theorem to prevent aliasing in cascaded moving averages.
- RAIN (Rainbow Moving Average): Combines multiple SMA layers with weighted averages for multi-scale smoothing.
- TRAMA (Trend Regularity Adaptive Moving Average): Adapts smoothing based on the frequency of new highs and lows in price data.
- Implemented Vortex Indicator in Vortex.cs, including calculation logic and event handling.
- Added detailed documentation for Vortex Indicator in Vortex.md, covering historical context, algorithm, outputs, and trading interpretation.
- Updated oscillators index to include TTM Wave indicator.
- Added TTM Wave documentation with algorithm and trading interpretation.
- Updated reversals index to include TTM Scalper Alert indicator.
- Added TTM Scalper Alert documentation with algorithm and trading strategy.
- Updated NDepend badges to reflect increased code metrics (classes, methods, lines of code, public types, comments, and complexity).
Miha Kralj