Struct BlackScholesProcess 

pub struct BlackScholesProcess<'a> { /* private fields */ }

Risk-neutral lognormal dynamics dS = (r - q) S dt + sigma(S, t) S dW with constant or local volatility.

evolve is overridden so each step costs one volatility lookup shared by drift and diffusion (a local-vol lookup is several surface interpolations); the trait’s coefficient methods expose the same dynamics to generic consumers.

Implementations

impl<'a> BlackScholesProcess<'a>

pub fn new(drift_rate: f64, vol: VolDynamics<'a>) -> Self

pub fn vol(&self, s: f64, t: f64) -> f64

The volatility used to diffuse at level s, time t.

Trait Implementations

impl StochasticProcess1D for BlackScholesProcess<'_>

fn constrain(&self, x: f64) -> f64

A lognormal spot cannot go negative; approximate schemes can.

fn drift(&self, _t: f64, x: f64) -> f64

Drift coefficient a(t, x).

fn diffusion(&self, t: f64, x: f64) -> f64

Diffusion coefficient b(t, x).

fn diffusion_dx(&self, t: f64, x: f64) -> f64

∂b/∂x, the extra coefficient Milstein needs.

fn exact_step(&self, t: f64, x: f64, dt: f64, dw: f64) -> Option<f64>

One draw from the closed-form transition X_{t+dt} | X_t = x, when the process has one. None (the default) makes the Exact scheme fall back to Euler.

fn evolve( &self, scheme: DiscretizationScheme, t: f64, x: f64, dt: f64, dw: f64, ) -> f64

Advance the state by one step of scheme: the generic stepping, written against drift/diffusion alone. Override only to exploit model structure (e.g. one volatility lookup shared by the coefficients, or a scheme the enum cannot express).