Euler end-point discretization for stochastic processes. More...

#include <ql/processes/endeulerdiscretization.hpp>

Inheritance diagram for EndEulerDiscretization:

Public Member Functions
Disposable< Array >	drift (const StochasticProcess &, Time t0, const Array &x0, Time dt) const

Real	drift (const StochasticProcess1D &, Time t0, Real x0, Time dt) const

Disposable< Matrix >	diffusion (const StochasticProcess &, Time t0, const Array &x0, Time dt) const

Real	diffusion (const StochasticProcess1D &, Time t0, Real x0, Time dt) const

Disposable< Matrix >	covariance (const StochasticProcess &, Time t0, const Array &x0, Time dt) const

Real	variance (const StochasticProcess1D &, Time t0, Real x0, Time dt) const

Detailed Description

Euler end-point discretization for stochastic processes.

Member Function Documentation

virtual

Returns an approximation of the drift defined as $\mu(t_0 + \Delta t, \mathbf{x}_0) \Delta t$ .

virtual

Returns an approximation of the drift defined as $\mu(t_0 + \Delta t, x_0) \Delta t$ .

Disposable<Matrix> diffusion	(	const StochasticProcess &	,
		Time	t0,
		const Array &	x0,
		Time	dt
	)		const

virtual

Returns an approximation of the diffusion defined as $\sigma(t_0 + \Delta t, \mathbf{x}_0) \sqrt{\Delta t}$ .

virtual

Returns an approximation of the diffusion defined as $\sigma(t_0 + \Delta t, x_0) \sqrt{\Delta t}$ .

Disposable<Matrix> covariance	(	const StochasticProcess &	,
		Time	t0,
		const Array &	x0,
		Time	dt
	)		const

virtual

Returns an approximation of the covariance defined as $\sigma(t_0 + \Delta t, \mathbf{x}_0)^2 \Delta t$ .

virtual

Returns an approximation of the variance defined as $\sigma(t_0 + \Delta t, x_0)^2 \Delta t$ .