2.5.4. sdepy.hull_white_process

class sdepy.hull_white_process(paths=1, vshape=(), dtype=None, steps=None, i0=0, info=None, getinfo=True, method='euler', factors=1, x0=0., theta=0., k=1., sigma=1., dw=None, corr=None, rho=None)

F-factors Hull-White process (sum of F correlated mean-reverting Brownian motions).

Generates a process x(t) that solves the following SDE:

x(t) = y_1(t) + ... + y_F(t)
dy_i(t) = k_i(t)*(theta_i(t) - y_i(t))*dt +
          + sigma_i(t)*dw_i(t, dt)

where dw_i(t, dt) are standard Wiener process increments with correlations dw_i(t, dt)*dw_j(t, dt) = corr(t)[i, j]. x0, SDE parameters and dw(t, dt) should broadcast to vshape + (factors, paths).

Parameters:

paths, vshape, dtype, steps, i0, info, getinfo, method

See SDE class documentation.

x0 : array-like

Initial condition.

theta, k, sigma : array-like, or callable

SDE parameters.

dw, corr, rho

Specification of stochasticity source of Wiener process increments. See SDE.source_dw documentation.

See also

SDE

SDE.source_dw

wiener_source

hull_white_SDE

ornstein_uhlenbeck_process

Attributes:

See SDE class documentation.

Methods

See SDE class documentation.