Implementation:Avhz RustQuant GeometricBrownianMotion new

Knowledge Sources	RustQuant
Domains	Stochastic_Processes, Monte_Carlo
Last Updated	2026-02-07 20:00 GMT

Overview

Concrete tool for instantiating a Geometric Brownian Motion stochastic process provided by the RustQuant stochastics crate.

Description

The GeometricBrownianMotion struct implements the StochasticProcess trait with drift = mu * x and diffusion = sigma * x. Parameters can be either constant f64 values or time-dependent closures via the ModelParameter type. The process has no jump component.

Usage

Import this struct when you need to simulate asset price paths for Monte Carlo pricing or when modeling equity/index dynamics. Combine with StochasticProcessConfig and call generate() to produce sample paths.

Code Reference

Source Location

• Repository: RustQuant
• File: crates/RustQuant_stochastics/src/geometric_brownian_motion.rs
• Lines: L14-63

Signature

pub struct GeometricBrownianMotion {
    pub mu: ModelParameter,
    pub sigma: ModelParameter,
}

impl GeometricBrownianMotion {
    pub fn new(mu: impl Into<ModelParameter>, sigma: impl Into<ModelParameter>) -> Self
    pub fn parameters(&self) -> Vec<f64>
    pub fn unpack(&self) -> (f64, f64)
}

impl StochasticProcess for GeometricBrownianMotion {
    fn drift(&self, x: f64, t: f64) -> f64    // mu(t) * x
    fn diffusion(&self, x: f64, t: f64) -> f64 // sigma(t) * x
    fn jump(&self, _x: f64, _t: f64) -> Option<f64> // None
}

Import

use RustQuant::stochastics::GeometricBrownianMotion;

I/O Contract

Inputs

Name	Type	Required	Description
mu	impl Into<ModelParameter>	Yes	Drift parameter (f64 or Fn(f64)->f64)
sigma	impl Into<ModelParameter>	Yes	Volatility parameter (f64 or Fn(f64)->f64)

Outputs

Name	Type	Description
return	GeometricBrownianMotion	A process implementing StochasticProcess trait, ready for path generation

Usage Examples

Constant Parameters

use RustQuant::stochastics::{
    GeometricBrownianMotion, StochasticProcess,
    StochasticProcessConfig, StochasticScheme,
};

// Create GBM with constant drift=5% and vol=20%
let gbm = GeometricBrownianMotion::new(0.05, 0.20);

// Configure simulation
let config = StochasticProcessConfig::new(
    100.0,  // initial price
    0.0,    // start time
    1.0,    // end time (1 year)
    252,    // daily steps
    StochasticScheme::EulerMaruyama,
    10_000, // number of paths
    true,   // parallel execution
    None,   // no seed (random)
);

// Generate paths
let trajectories = gbm.generate(&config);
println!("Generated {} paths", trajectories.paths.len());

For Monte Carlo Pricing

use RustQuant::stochastics::GeometricBrownianMotion;

// For risk-neutral MC pricing, use risk-free rate as drift
let interest_rate = 0.05;
let volatility = 0.20;
let process = GeometricBrownianMotion::new(interest_rate, volatility);

Related Pages

Implements Principle

• Principle:Avhz_RustQuant_Geometric_Brownian_Motion

Requires Environment

• Environment:Avhz_RustQuant_Rust_Stable