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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/momentum/bias/Bias.md
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# BIAS: Price Deviation from Moving Average (also known as Disparity Index)
> *When traders ask 'how overbought is it?', they're really asking how far price has strayed from its anchor. Bias answers that question in percentage terms, telling you whether the current price is 5% above or 10% below its moving average. It's the market's stretch marks made visible.*
| Property | Value |
| ---------------- | -------------------------------- |
| **Category** | Momentum |
@@ -16,8 +18,6 @@
- Requires `period` bars of warmup before first valid output (IsHot = true).
- Validated against TA-Lib, Skender, and Tulip reference implementations where available.
> "When traders ask 'how overbought is it?', they're really asking how far price has strayed from its anchor. Bias answers that question in percentage terms, telling you whether the current price is 5% above or 10% below its moving average. It's the market's stretch marks made visible."
The Bias indicator measures the percentage difference between the current price and its Simple Moving Average (SMA). A positive bias indicates price is above the average (potentially overbought), while negative bias suggests price is below average (potentially oversold). This is one of the simplest yet most effective tools for identifying mean-reversion opportunities.
## Historical Context