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HestonProcess

market_model::process::heston

Struct HestonProcess 

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pub struct HestonProcess {
    pub mu: f64,
    pub kappa: f64,
    pub theta: f64,
    pub sigma: f64,
    pub rho: f64,
    pub price: f64,
    pub variance: f64,
    /* private fields */
}
Expand description

Heston stochastic volatility model.

$$dS_t = mu * S_t * dt + sqrt(v_t) * S_t * dW_t^S$$ $$dv_t = kappa * (theta - v_t) * dt + sigma * sqrt(v_t) * dW_t^v$$

with correlation rho between the two Brownian motions.

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§mu: f64§kappa: f64§theta: f64§sigma: f64§rho: f64§price: f64§variance: f64

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impl HestonProcess

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pub fn new( mu: f64, kappa: f64, theta: f64, sigma: f64, rho: f64, initial_price: f64, initial_variance: f64, ) -> Self

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pub fn price(&self) -> f64

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pub fn volatility(&self) -> f64

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

Closed-form expected variance.

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

Closed-form variance of variance.

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impl Clone for HestonProcess

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fn clone(&self) -> HestonProcess

Returns a duplicate of the value. Read more
1.0.0 (const: unstable) · Source§

fn clone_from(&mut self, source: &Self)

Performs copy-assignment from source. Read more
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impl Simulatable for HestonProcess

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type Output = (f64, f64)

The type emitted at each step (e.g. f64 for GBM, BookSnapshot for L3).
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fn dim(&self) -> usize

Dimensionality of the Brownian driver. Used by the runner to pre-generate the correct number of random normals per step. GBM is 1, Heston is 2, etc.
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fn step(&mut self, dt: f64, dw: &[f64], _rng: &mut impl Rng) -> (f64, f64)

Advance the model by one step of size dt. Read more
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fn current(&self) -> (f64, f64)

The current state snapshot. Called once before simulation starts.
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impl StochasticProcess for HestonProcess

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type State = ArrayBase<OwnedRepr<f64>, Dim<[usize; 1]>>

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type Diffusion = ArrayBase<OwnedRepr<f64>, Dim<[usize; 2]>>

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type BrownianIncrement = ArrayBase<OwnedRepr<f64>, Dim<[usize; 1]>>

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fn drift(&self, x: &Array1<f64>, _t: f64) -> Array1<f64>

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fn diffusion(&self, x: &Array1<f64>, _t: f64) -> Array2<f64>

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fn jump_size<R: Rng + ?Sized>( &self, x: &Array1<f64>, _t: f64, _rng: &mut R, ) -> Array1<f64>

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fn expected_value(&self, x0: &Array1<f64>, t: f64) -> Array1<f64>

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fn variance(&self, x0: &Array1<f64>, t: f64) -> Array1<f64>

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fn step<R: Rng + ?Sized>( &self, x: &Array1<f64>, t: f64, dt: f64, dw: &Array1<f64>, _rng: &mut R, ) -> Array1<f64>

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fn generate_increment<R: Rng + ?Sized>( &self, rng: &mut R, dt: f64, ) -> Array1<f64>

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fn simulate<R: Rng + ?Sized>( &self, x0: Array1<f64>, t0: f64, t_end: f64, dt: f64, rng: &mut R, ) -> Vec<(f64, Array1<f64>)>

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fn jump_intensity(&self, _x: &Self::State, _t: f64) -> f64

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fn simulate_paths( &self, x0: Self::State, t0: f64, t_end: f64, dt: f64, num_paths: usize, ) -> Vec<Vec<(f64, Self::State)>>
where Self: Sync, Self::State: Send + Sync + Clone,

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unsafe fn clone_to_uninit(&self, dest: *mut u8)

🔬This is a nightly-only experimental API. (clone_to_uninit)
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