VIDYA indicator with adaptive smoothing based on market volatility.

lib/feeds/csv/CsvFeed.md

@@ -18,6 +18,7 @@ The file must have a header row and follow this column order:
 - **Prices/Volume**: Numeric values
 
 Example:
+
 ```csv
 Date,Open,High,Low,Close,Volume
 2024-01-01,100.0,105.0,99.0,102.5,10000
@@ -38,11 +39,13 @@ public class CsvFeed : IFeed
 ## Usage
 
 ### 1. Loading Data
+
 ```csharp
 var feed = new CsvFeed("path/to/data.csv");
 ```
 
 ### 2. Streaming Data (Simulation)
+
 ```csharp
 // Get first bar
 var bar = feed.Next(isNew: true);
@@ -63,6 +66,7 @@ while (true)
 ```
 
 ### 3. Fetching a Batch
+
 ```csharp
 long startTime = new DateTime(2024, 1, 1).Ticks;
 var batch = feed.Fetch(10, startTime, TimeSpan.FromDays(1));

lib/feeds/gbm/GBM.md

@@ -17,6 +17,7 @@ The price evolution follows the stochastic differential equation:
 $$ dS_t = \mu S_t dt + \sigma S_t dW_t $$
 
 Where:
+
 - $S_t$: Asset price at time $t$
 - $\mu$: Drift (expected return)
 - $\sigma$: Volatility (standard deviation of returns)
@@ -37,6 +38,7 @@ public class GBM : IFeed
 ## Usage
 
 ### 1. Initialization
+
 ```csharp
 // Default: Start at 100, 5% drift, 20% volatility
 var gbm = new GBM();
@@ -46,6 +48,7 @@ var volatileGbm = new GBM(startPrice: 50.0, mu: 0.10, sigma: 0.50);
 ```
 
 ### 2. Streaming Generation
+
 ```csharp
 // Generate a new bar
 var bar = gbm.Next(isNew: true);
@@ -59,6 +62,7 @@ for (int i = 0; i < 5; i++)
 ```
 
 ### 3. Batch Generation
+
 ```csharp
 long startTime = DateTime.UtcNow.Ticks;
 var interval = TimeSpan.FromMinutes(1);