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eta: G2 stochastic process

NAME

QuantLib::G2Process - G2 stochastic process

SYNOPSIS

#include <ql/processes/g2process.hpp>

Inherits QuantLib::StochasticProcess.

Public Member Functions

G2Process (Real a, Real sigma, Real b, Real eta, Real rho)

Real x0 () const

Real y0 () const

Real a () const

Real sigma () const

Real b () const

Real eta () const

Real rho () const

StochasticProcess interface

Size size () const
returns the number of dimensions of the stochastic process
Disposable< Array > initialValues () const
returns the initial values of the state variables
Disposable< Array > drift (Time t, const Array &x) const
returns the drift part of the equation, i.e., $ mu(t, mathrm{x}_t) $
Disposable< Matrix > diffusion (Time t, const Array &x) const
returns the diffusion part of the equation, i.e. $ igma(t, mathrm{x}_t) $
Disposable< Array > expectation (Time t0, const Array &x0, Time dt) const

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

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

Detailed Description

G2 stochastic process

Member Function Documentation

Disposable<Array> expectation (Time t0, const Array & x0, Time dt) const [virtual]

returns the expectation $ E(mathrm{x}_{t_0 + Delta t} | mathrm{x}_{t_0} = mathrm{x}_0) $ of the process after a time interval $ Delta t $ according to the given discretization. This method can be overridden in derived classes which want to hard-code a particular discretization.

Reimplemented from StochasticProcess.

Disposable<Matrix> stdDeviation (Time t0, const Array & x0, Time dt) const [virtual]

returns the standard deviation $ S(mathrm{x}_{t_0 + Delta t} | mathrm{x}_{t_0} = mathrm{x}_0) $ of the process after a time interval $ Delta t $ according to the given discretization. This method can be overridden in derived classes which want to hard-code a particular discretization.

Reimplemented from StochasticProcess.

Disposable<Matrix> covariance (Time t0, const Array & x0, Time dt) const [virtual]

returns the covariance $ V(mathrm{x}_{t_0 + Delta t} | mathrm{x}_{t_0} = mathrm{x}_0) $ of the process after a time interval $ Delta t $ according to the given discretization. This method can be overridden in derived classes which want to hard-code a particular discretization.

Reimplemented from StochasticProcess.

Author

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