- 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 Standardize class for calculating Z-Score normalization over a specified lookback period.
- Updated NDepend badge SVG files to reflect new metrics.
- Modified NDepend project files to reference the updated solution file name.
- Removed outdated documentation files related to indicator proposals and channel documentation remediation.
- Updated workspace configuration to point to the new solution file.
- 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).
- Implemented ChopIndicator for Quantower with configurable period and cold value display.
- Created Chop class for calculating the Choppiness Index with detailed documentation.
- Added comprehensive unit tests for Chop functionality, covering various market conditions and edge cases.
- Developed markdown documentation for CHOP, detailing its historical context, mathematical foundation, and usage examples.
- Established a remediation plan for channel indicators documentation, identifying gaps and prioritizing updates.
- 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 CCV class for calculating annualized log return volatility using SMA, EMA, and WMA smoothing methods.
- Added comprehensive unit tests for CCV to validate mathematical correctness, consistency across methods, and edge cases.
- Created documentation for CCV detailing its mathematical foundation, smoothing methods, and performance metrics.
- 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.
- Updated Codacy instructions to streamline usage guidelines.
- Refactored Bbands class to utilize ArrayPool for memory management, preventing stack overflow on large series.
- Changed Fcb class to use long for monotonic deques to avoid truncation issues.
- Enhanced Kchannel class to ensure safe defaults for non-finite values.
- Improved Maenv class to prevent double-priming during calculations.
- Modified Mmchannel class to ensure non-negative buffer indices and removed unnecessary state tracking.
- Updated Pchannel class to correctly reference IsHot state.
- Refined Regchannel class to avoid double-processing during calculations.
- Enhanced Starchannel class to sanitize non-finite values during calculations.
- Adjusted Stbands.Quantower.cs to allow finer control over multiplier precision.
- Updated Ubands class to only update last valid values on new bars.
- Modified Uchannel.Quantower.cs to allow for finer multiplier precision.
- Enhanced Vwapbands classes to include standard deviation calculations and ensure consistent array lengths.
- Refactored Vwapsd classes to include standard deviation outputs and ensure consistent array lengths.
- Updated MonotonicDeque to use long for indices to prevent overflow.
- Improved Mdape class to handle zero actual values with a substitute value for error calculation.
- Enhanced Rae class to ensure correct state management during updates.
- Refined Wmape class to simplify the logic for finding last valid actual and predicted values.
- Updated Cmf.Quantower classes to ensure MinHistoryDepths reflects the current period.
- Updated buffer handling in TheilU and Wmape classes to ensure consistency after adding new values.
- Changed the resync interval constant in TukeyBiweight for better clarity.
- Refactored state structures to record structs in Gauss, Hann, Hp, Hpf, Kalman, Loess, Notch, and other filter classes for improved performance and readability.
- Enhanced numerical stability in Mama class calculations using Fused Multiply-Add (FMA) for precision.
- Added comprehensive tests for Atan2 validation to compare .NET's Math.Atan2 with PineScript's implementation, ensuring accuracy across various edge cases.
- Updated NDepend badges to reflect changes in classes, methods, and lines of code.
- 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.
- Disabled symbol package generation (IncludeSymbols=false)
- Removed JetBrains.Annotations dependency from Directory.Build.props
- Changed QuanTAlib package to target net10.0 only (net8.0 remains for Quantower wrappers)
- Introduced a new CodeQL extension for C# in `.github/codeql/extensions/quantalib-csharp/codeql-pack.yml`.
- Added SonarLint configuration in `.sonarlint/CSharp/SonarLint.xml` and `.sonarlint/csharp.ruleset` to suppress specific rules for high-performance indicators.
- Removed outdated `.vscode/launch.json` configurations.
- Updated `.vscode/tasks.json` to streamline build and test tasks, including renaming and consolidating tasks.
- Modified `Directory.Build.props` to enhance SARIF output directory handling and integrate SonarLint rules.
- Refactored various indicator classes to improve code clarity and maintainability, including updates to method parameters for consistency.
- Added XML documentation comments to several classes and methods for better code understanding.
- Improved numerical stability in calculations by replacing direct comparisons with `double.Epsilon` checks in multiple classes.
- 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