4 Commits

Author SHA1 Message Date
Miha Kralj 67ad6f0cba v0.8.7: Replace periodic ResyncInterval with Kahan compensated summation
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
2026-03-13 22:01:31 -07:00
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 6d6259a47d normalization of methods 2026-02-10 21:33:16 -08:00
Miha Kralj bcb52ef5ec Add Close-to-Close Volatility (CCV) implementation and validation tests
- 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.
2026-01-31 17:25:39 -08:00