Commit Graph

6 Commits

Author SHA1 Message Date
Miha Kralj 1910fdca93 chore: repo cleanup and code quality improvements
- Remove global.json (SDK pinning unnecessary)

- Remove nuget.config, move MyGet source to .csproj RestoreAdditionalProjectSources

- Gitignore ndepend/ entirely, move badges to docs/img/

- Update README.md and docs/ndepend.md badge paths

- Add NDepend project property to QuanTAlib.slnx

- Expand .editorconfig ReSharper/diagnostic suppressions

- Use ArgumentOutOfRangeException instead of ArgumentException

- Use discard _ for unused event sender parameters

- Remove quantalib.code-workspace and sonar-suppressions.json

- Add filter signature SVGs
2026-03-03 09:22:55 -08:00
Miha Kralj 83e9511261 python wrapper 2026-02-28 14:14:35 -08:00
Miha Kralj 4ab3a7fb53 doc headers 2026-02-27 07:48:12 -08:00
Miha Kralj 8a1ba95173 validation and profiles 2026-02-26 22:02:52 -08:00
Miha Kralj 9ab37c1200 adding missing validations 2026-02-26 09:59:44 -08:00
Miha Kralj 90d5638008 Add new moving average implementations: LTMA, MCNMA, NLMA, NMA, NYQMA, RAIN, and TRAMA
- 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.
2026-02-20 21:40:32 -08:00