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Co-authored-by: Claude Opus 4.5 <noreply@anthropic.com> Co-authored-by: aider (openrouter/anthropic/claude-sonnet-4) <aider@aider.chat> Co-authored-by: Warp <agent@warp.dev>
72 lines
2.0 KiB
Markdown
72 lines
2.0 KiB
Markdown
# GBM Class
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`GBM` (Geometric Brownian Motion) is a synthetic data generator that simulates realistic financial price movements. It is useful for testing indicators, strategies, and system performance without relying on external data files.
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## Key Features
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* **Geometric Brownian Motion**: Uses the standard mathematical model for asset price dynamics.
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* **Configurable Parameters**: Control drift (trend) and volatility (noise).
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* **Stateless Design**: Minimal memory footprint; only maintains state needed for continuity.
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* **Dual Modes**: Supports both streaming (bar-by-bar) and batch generation.
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* **Intra-bar Updates**: Can simulate real-time price updates within a single bar.
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## Mathematical Model
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The price evolution follows the stochastic differential equation:
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$$ dS_t = \mu S_t dt + \sigma S_t dW_t $$
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Where:
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* $S_t$: Asset price at time $t$
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* $\mu$: Drift (expected return)
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* $\sigma$: Volatility (standard deviation of returns)
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* $W_t$: Wiener process (Brownian motion)
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## Class Definition
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```csharp
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public class GBM : IFeed
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{
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public GBM(double startPrice = 100.0, double mu = 0.05, double sigma = 0.2, TimeSpan? defaultTimeframe = null);
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public TBar Next(bool isNew = true);
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public TBarSeries Fetch(int count, long startTime, TimeSpan interval);
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}
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```
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## Usage
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### 1. Initialization
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```csharp
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// Default: Start at 100, 5% drift, 20% volatility
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var gbm = new GBM();
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// Custom: Start at 50, 10% drift, 50% volatility
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var volatileGbm = new GBM(startPrice: 50.0, mu: 0.10, sigma: 0.50);
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```
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### 2. Streaming Generation
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```csharp
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// Generate a new bar
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var bar = gbm.Next(isNew: true);
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// Simulate intra-bar updates (e.g., real-time ticks)
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for (int i = 0; i < 5; i++)
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{
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var updatedBar = gbm.Next(isNew: false);
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Console.WriteLine($"Update: {updatedBar.Close}");
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}
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```
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### 3. Batch Generation
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```csharp
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long startTime = DateTime.UtcNow.Ticks;
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var interval = TimeSpan.FromMinutes(1);
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// Generate 1000 bars
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var history = gbm.Fetch(1000, startTime, interval);
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