Struct HestonProcess 

pub struct HestonProcess {
    pub drift_rate: f64,
    pub params: HestonParams,
    pub scheme: HestonScheme,
}

Heston dynamics as a 2-state, 2-factor process, state [S, v]:

dS = (r - q) S dt + sqrt(v) S dW_s
dv = kappa (theta - v) dt + vol_of_vol sqrt(v) dW_v

dw carries independent increments; the spot/variance correlation is applied inside — through the Cholesky rows of the diffusion matrix for full truncation, analytically through the K1/K2 coefficients for QE. evolve overrides the generic Euler with the selected HestonScheme.

Fields

drift_rate: f64

Risk-neutral drift rate r - q.

params: HestonParams

scheme: HestonScheme

Trait Implementations

impl StochasticProcess for HestonProcess

fn dim(&self) -> usize

Number of state variables.

fn factors(&self) -> usize

Number of driving Brownian factors (dw.len()).

fn drift(&self, _t: f64, x: &[f64], out: &mut [f64])

Drift vector a(t, x) into out (dim long).

fn diffusion(&self, _t: f64, x: &[f64], out: &mut [f64])

Diffusion matrix b(t, x) into out, row-major dim × factors.

fn evolve(&self, _t: f64, x: &[f64], dt: f64, dw: &[f64], out: &mut [f64])

One Euler-Maruyama step from x into out. The default allocates small scratch buffers; hot loops should override with model-specific stepping (which is also where non-Euler schemes — exact transitions, Heston full-truncation/QE — live, since generic multi-factor Milstein would need Lévy areas).

fn constrain(&self, _x: &mut [f64])

State constraint applied after every step (identity by default).