feat: Add Cumulative Moving Average (CMA) implementation with detailed documentation

- Introduced Cma class for calculating the Cumulative Moving Average using Welford's algorithm with FMA for precision.
- Added methods for batch processing and streaming updates.
- Implemented a comprehensive markdown documentation for CMA, covering its mathematical foundation, performance profile, and use cases.
- Enhanced existing trend indicators (Bessel, Butter, Htit, Jma, Mama, Ssf, Vidya) with FMA for improved numerical stability and precision.
- Updated Adosc to utilize a single-pass algorithm for performance optimization.
- Fixed date initialization in benchmarks to ensure UTC consistency.

perf/Benchmark.cs

@@ -100,7 +100,7 @@ public class IndicatorBenchmarks
         {
             _quotes.Add(new Quote
             {
-                Date = new DateTime(_closeTseries.Times[i]),
+                Date = new DateTime(_closeTseries.Times[i], DateTimeKind.Utc),
                 Open = (decimal)bars.Open.Values[i],
                 High = (decimal)bars.High.Values[i],
                 Low = (decimal)bars.Low.Values[i],
@@ -115,7 +115,7 @@ public class IndicatorBenchmarks
         {
             _ooplesData.Add(new TickerData
             {
-                Date = new DateTime(_closeTseries.Times[i]),
+                Date = new DateTime(_closeTseries.Times[i], DateTimeKind.Utc),
                 Open = bars.Open.Values[i],
                 High = bars.High.Values[i],
                 Low = bars.Low.Values[i],