Stochastic Processes

This crate provides utilities for simulating various stochastic processes.

TODO:

The following features will by implemented in the near future:

• Wiener process (Brownian motion).
• Brownian bridge.
• Poisson process.
• Milstein method.

lib.rs:

Stochastic processes simluation toolkit.

This crate provides utilities for simulating various stochastic processes.

Quick Start

To create a process, call the new constructor for the desired process, and supply the constructor with the required parameters. To simulate a process, simply call simulate on the process.

In the following example, a Geometric Brownian motion is created with $\mu = \sigma = 1$. The processes is simluated using the Euler-Maruyama method. The path is stored inside of a SimulatedPath. Finally, the path is exported to a pickle file (for use in Python).

use stochastic_processes::prelude::*;

let proc = GeometricBrownianMotion {
    mu: 1.0,
    sigma: 1.0,
};

let sim = proc.run_euler_maruyama(1.0, 0.0, 1.0, 20);
let _ = export_to_pickle(sim, "/tmp/test.pickle").unwrap();