Comprehensive refactor across all indicators replacing the periodic
ResyncInterval-based drift correction (every 1000 ticks recalculate
from scratch) with Kahan compensated summation for running sums.
Key changes:
- Remove ResyncInterval constants and TickCount fields from all State records
- Add Kahan compensation fields (SumComp, SumSqComp, etc.) to State records
- Replace naive sum += val - removed with Kahan delta pattern
- Remove Resync()/RecalculateSum() methods that did O(N) recalculation
- Update batch/SIMD paths to use Kahan compensation instead of resync loops
- IIR filters (EMA, REMA, RGMA) simplified: inherently self-correcting
- Version bump to 0.8.7
- Build system: README version stamping via Directory.Build.props
- Minor doc/test tolerance adjustments for new numerical characteristics
Affected modules: channels, core, cycles, dynamics, errors, momentum,
oscillators, statistics, trends_FIR, trends_IIR, volatility, volume
Complete thin Dx-composition wrapper indicators with full test coverage:
- PlusDi/MinusDi: Directional Indicator wrappers (DiPlus/DiMinus from Dx)
- PlusDm/MinusDm: Directional Movement wrappers (DmPlus/DmMinus from Dx)
- Individual validation tests per indicator directory (TALib, Skender, bounds)
- Combined unit tests (DiDm.Tests.cs) and validation tests (DiDm.Validation.Tests.cs)
- Quantower wrappers + tests for all 4 indicators
- PineScript v6 implementations with compensated RMA
- Normalized .md documentation for all indicators and categories
- 182 tests passing, 0 failures
- 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.
- Implemented Prime method in Vel, Ao, Apo, Frama, Adl, Adosc, Aobv, Cmf, Efi, Eom, Iii, Kvo, Mfi, Nvi, Obv, Pvd, Pvi, Pvo, Pvr, Pvt, Tvi, Twap, Va, Vf, Vo, Vroc, Vwad, Vwap, and Vwma classes.
- The Prime method resets the indicator state and processes the provided historical bar data to initialize the indicator.
- Added warmup period property to Adl and Wad classes to define the minimum number of data points required for validity.
- Updated benchmark tests to use Batch methods for performance evaluation.
- 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.
- 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.
- 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.
- 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