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feat(dynamics): add PlusDI, MinusDI, PlusDM, MinusDM indicators

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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
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Miha Kralj
2026-03-11 20:21:52 -07:00
parent 56b86bebfb
commit 33d20f2a18
437 changed files with 4589 additions and 2792 deletions
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lib/statistics/cointegration/Cointegration.md
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# Cointegration: Engle-Granger Two-Step Cointegration Test
> *Correlation tells you they move together. Cointegration tells you they're bound together. Two stocks can be uncorrelated yet cointegrated, or perfectly correlated yet destined to drift apart forever. The difference between 'similar direction' and 'shared destiny' is the difference between a tourist attraction and a gravitational orbit.*
| Property | Value |
| ---------------- | -------------------------------- |
| **Category** | Statistic |
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- Requires `period + 1` bars of warmup before first valid output (IsHot = true).
- Validated against TradingView PineScript reference and statistical property tests.
> "Correlation tells you they move together. Cointegration tells you they're bound together. Two stocks can be uncorrelated yet cointegrated, or perfectly correlated yet destined to drift apart forever. The difference between 'similar direction' and 'shared destiny' is the difference between a tourist attraction and a gravitational orbit."
The Cointegration indicator measures the long-run equilibrium relationship between two price series using the Engle-Granger two-step method with an Augmented Dickey-Fuller (ADF) test. Unlike correlation, which measures short-term co-movement, cointegration tests whether two non-stationary series share a common stochastic trend—meaning they may diverge temporarily but are statistically bound to revert to their equilibrium relationship.
## Historical Context