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

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

lib/trends_IIR/yzvama/Yzvama.md

@@ -1,5 +1,7 @@
 # YZVAMA: Yang-Zhang Volatility Adjusted Moving Average
 
+> *ATR tells you how much the market moved. Yang-Zhang tells you how much it *should* have moved given the gaps and intrabar action. YZVAMA uses that distinction to know when the market is lying about its volatility.*
+
 | Property         | Value                            |
 | ---------------- | -------------------------------- |
 | **Category**     | Trend (IIR MA)                        |
@@ -16,8 +18,6 @@
 - Requires 1 bar of warmup before first valid output (IsHot = true).
 - Validated against TA-Lib, Skender, and Tulip reference implementations where available.
 
-> "ATR tells you how much the market moved. Yang-Zhang tells you how much it *should* have moved given the gaps and intrabar action. YZVAMA uses that distinction to know when the market is lying about its volatility."
-
 ## The Core Insight
 
 Most adaptive moving averages measure volatility using close-to-close changes (standard deviation) or high-low ranges (ATR). Both approaches miss a critical market dynamic: overnight gaps. A stock that gaps up 5% at the open but closes unchanged shows zero close-to-close volatility, yet anyone trading that day felt every point of that 5% move.