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.
- 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 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.
- 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.
- 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