- Added detailed comments explaining the validation limitations for MMA and ZLEMA due to differences in algorithm implementations.
- Implemented validation tests for True Range against TALib and Tulip, ensuring directional agreement.
- Updated Ulcer Index validation to clarify differences in algorithmic approaches between QuanTAlib and Skender.
- Enhanced Ease of Movement tests to verify directional agreement with Tulip's EMV, noting differences in volume scaling.
- Expanded Klinger Volume Oscillator tests to validate against Skender and Tulip, focusing on directional agreement across multiple period configurations.
- Improved Negative Volume Index tests to compare percentage changes with Tulip, addressing differences in starting values.
- Updated Positive Volume Index tests to validate against Tulip, emphasizing percentage change comparisons.
- Enhanced Williams Accumulation/Distribution tests to verify directional agreement with Tulip, highlighting formula differences.
- Implemented the SSF-DSP (Super Smooth Filter Detrended Synthetic Price) indicator using dual Super Smooth Filters.
- Added validation tests to ensure correctness against PineScript implementation and mathematical properties.
- Created comprehensive documentation outlining the architecture, mathematical foundation, performance profile, and common pitfalls.
- Included batch processing capabilities for efficient calculations on time series data.
- 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 the PvtIndicator class for calculating Price Volume Trend in Quantower.
- Created unit tests for the Pvt class to validate calculations and state management.
- Added validation tests to ensure consistency with OoplesFinance's implementation.
- Developed a comprehensive documentation (Pvt.md) explaining the PVT concept, calculations, and usage.
- Included methods for batch calculations and streaming updates for PVT.
- Implemented NVI indicator in Nvi.Quantower.cs with configurable start value and cold value display option.
- Created unit tests for NVI functionality in Nvi.Tests.cs, covering various scenarios including initialization, updates, and edge cases.
- Added validation tests in Nvi.Validation.Tests.cs to ensure NVI matches expected behavior against known implementations.
- Developed comprehensive documentation for NVI in Nvi.md, detailing its historical context, mathematical foundation, and interpretation guide.
- Included error handling for invalid input values and ensured compatibility with volume data.
- Implemented the III indicator in Iii.Quantower.cs, measuring buying/selling pressure based on close price within the day's range, weighted by volume.
- Added unit tests for III functionality in Iii.Tests.cs, covering various scenarios including default parameters, updates, and cumulative mode.
- Created validation tests in Iii.Validation.Tests.cs to ensure consistency between streaming, batch, and span calculations.
- Developed comprehensive documentation for III in Iii.md, detailing its historical context, mathematical foundation, and common pitfalls.
- 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 the Starchannel class, which calculates a volatility-based envelope using SMA as the middle line and ATR for band width.
- Added methods for updating the indicator with new data, batch calculations, and state management.
- Created comprehensive unit tests for the Starchannel indicator, validating various scenarios including manual calculations, consistency across modes, eventing, and handling of large datasets.
- Ensured that the indicator's outputs are finite and that band widths are consistent across different calculation modes.
- 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