- 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 SgmaIndicator class in C# with properties for Period, Degree, and Source.
- Added unit tests for SgmaIndicator covering constructor defaults, initialization, and various update scenarios.
- Created a new Quantower adapter for the SGMA indicator, including input parameters and line series setup.
- Removed legacy SGMA implementation and tests to streamline the codebase.
- Updated project files to include new indicator and tests in the build process.
- Generated a missing indicators report and outlined a plan for oscillator documentation rewrite.
Miha Kralj