- 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.
- Updated the name and description of the Hilbert Trendline (HTIT) to "Ehlers Hilbert Transform Instantaneous Trend (HTIT)".
- Changed the name and description of the MESA Adaptive Moving Average (MAMA) to "Ehlers MESA Adaptive Moving Average".
- Modified the Center of Gravity (CG) indicator to "Ehlers Center of Gravity (CG)".
- Renamed the Detrended Synthetic Price (DSP) to "Ehlers Detrended Synthetic Price (DSP)".
- Updated the Autocorrelation Periodogram (EACP) to "Ehlers Autocorrelation Periodogram (EACP)".
- Changed the Homodyne Discriminator (HOMOD) to "Ehlers Homodyne Discriminator (HOMOD)".
- Updated the Hilbert Transform Dominant Cycle Period and Phase indicators to include "Ehlers" in their names.
- Renamed the Hilbert Transform Phasor Components to "Ehlers Hilbert Transform Phasor Components (HT_PHASOR)".
- Updated the SineWave indicator to "Ehlers Hilbert Transform SineWave (HT_SINE)".
- Changed the Phasor Analysis indicator to "Ehlers Hilbert Transform Phasor Components (HT_PHASOR)".
- Updated the SSF-Based Detrended Synthetic Price to "Ehlers SSF Detrended Synthetic Price (SSFDSP)".
- Renamed the Ultimate Channel to "Ehlers Ultimate Channel (UCHANNEL)".
- Added new indicators: Moving Average Variable Period (MAVP), Ehlers Predictive Moving Average (PMA), Ehlers Reverse EMA (REVERSEEMA), and Ehlers Trendflex Indicator (TRENDFLEX).
- Updated various SVG badges to reflect changes in classes, comments, source files, lines of code, methods, and public types.
- Updated class count in classes.svg from 938 to 1078.
- Adjusted comments percentage in comments.svg from 33.06 to 33.02.
- Revised average cyclomatic complexity in complexity.svg from 2.19 to 2.12.
- Increased source files count in files.svg from 1099 to 1275.
- Updated lines of code in loc.svg from 114549 to 129859.
- Increased methods count in methods.svg from 12035 to 14066.
- Updated public types count in public-api.svg from 1086 to 1225.
- Revised missing indicators report with updated counts and categories, reflecting recent implementations and planned additions.
- Introduced YZV class for calculating Yang-Zhang Volatility, a comprehensive volatility measure that incorporates overnight, open-to-close, and high-low components.
- Implemented calculation methods, including batch processing for TBarSeries and spans.
- Added documentation for YZV, detailing its mathematical foundation, performance profile, and trading applications.
- Updated volume index documentation to reflect changes in file paths.
- Refactored VWMA calculation method to use a more generic source parameter instead of price.
- Implemented Vwapsd class for calculating VWAP with configurable standard deviation bands.
- Added methods for updating the indicator with new bars and calculating VWAPSD using both bar series and span arrays.
- Created comprehensive validation tests for VWAPSD, including checks for consistency between streaming and batch modes, mathematical correctness, and handling of edge cases such as NaN values and zero volume bars.
- Ensured that the implementation adheres to performance standards with tests for large datasets and fractional numDevs values.
- Implemented CMF indicator in Cmf.cs with detailed calculations and methods.
- Created unit tests for CMF validation against Skender, Ooples, and batch processing.
- Added documentation for CMF in Cmf.md, explaining its purpose, calculations, and usage.
- Updated project files to include new statistics library.
- Updated NDepend badges to reflect changes in classes, methods, and lines of code.
- Implemented Sdchannel class for calculating standard deviation channels based on linear regression.
- Added detailed documentation for SDCHANNEL, including overview, calculation methods, and interpretation.
- Updated project files to include new numerics library components in Channels and Volatility projects.
Miha Kralj