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Implementation:Avhz RustQuant HullWhite Process

From Leeroopedia


Knowledge Sources
Domains Stochastic_Processes, Quantitative_Finance
Last Updated 2026-02-07 19:00 GMT

Overview

Concrete implementation of the Hull-White (one-factor) short-rate model provided by the RustQuant library.

Description

The Hull-White model is a no-arbitrage, mean-reverting short-rate model defined by the SDE:

dX(t) = [theta(t) - alpha(t) * X(t)] dt + sigma(t) dW(t)

where alpha is the mean reversion speed, theta(t) is the time-dependent mean reversion function calibrated to fit the initial term structure, and sigma(t) is the volatility. The model extends the Vasicek model by allowing theta to be time-dependent, enabling exact calibration to the observed yield curve.

Key parameters:

  • alpha (ModelParameter) -- Mean reversion speed (long-run mean)
  • sigma (ModelParameter) -- Volatility (non-negative)
  • theta (ModelParameter) -- Mean reversion target function (non-negative)

Usage

Use this process for modeling short rates when you need a calibrated no-arbitrage model for interest rate derivative pricing. The Hull-White model is one of the most widely used short-rate models in practice, balancing analytical tractability with the ability to fit the current term structure.

Code Reference

Source Location

Signature

pub struct HullWhite {
    pub alpha: ModelParameter,
    pub sigma: ModelParameter,
    pub theta: ModelParameter,
}

impl HullWhite {
    pub fn new(
        alpha: impl Into<ModelParameter>,
        sigma: impl Into<ModelParameter>,
        theta: impl Into<ModelParameter>,
    ) -> Self
}

impl StochasticProcess for HullWhite {
    fn drift(&self, x: f64, t: f64) -> f64
    fn diffusion(&self, _x: f64, t: f64) -> f64
    fn jump(&self, _x: f64, _t: f64) -> Option<f64>
    fn parameters(&self) -> Vec<f64>
}

Import

use RustQuant::stochastics::HullWhite;

I/O Contract

Inputs

Name Type Required Description
alpha impl Into<ModelParameter> Yes Mean reversion speed
sigma impl Into<ModelParameter> Yes Volatility (non-negative)
theta impl Into<ModelParameter> Yes Mean reversion target function

Outputs

Name Type Description
drift() f64 Returns theta(t) - alpha(t) * x -- mean-reverting drift
diffusion() f64 Returns sigma(t) -- the diffusion component
jump() Option<f64> Always returns None (no jump component)
parameters() Vec<f64> Returns [alpha(0), sigma(0), theta(0)]

Usage Examples

use RustQuant::stochastics::HullWhite;
use RustQuant::stochastics::{StochasticProcessConfig, StochasticScheme};

// Create a Hull-White process with alpha=2.0, sigma=2.0, theta=0.5
let hw = HullWhite::new(2.0, 2.0, 0.5);

// Configure simulation: x0=10.0, t_start=0.0, t_end=1.0, n_steps=150, 1000 paths
let config = StochasticProcessConfig::new(
    10.0, 0.0, 1.0, 150, StochasticScheme::EulerMaruyama, 1000, false, None
);

let output = hw.generate(&config);

// Access simulated paths
let paths = &output.paths;

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