QuantLib::StochasticProcessArray

StochasticProcessArray Class Reference

#include <ql/Processes/stochasticprocessarray.hpp>

Inheritance diagram for StochasticProcessArray:

Detailed Description

Array of correlated 1-D stochastic processes.

Public Member Functions

StochasticProcessArray (const std::vector< boost::shared_ptr< StochasticProcess1D > > &, const Matrix &correlation)

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. $\sigma(t, \mathrm{x}_t)$

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

Disposable< Array > apply (const Array &x0, const Array &dx) const

Time time (const Date &) const

const boost::shared_ptr< StochasticProcess1D > & process (Size i) const

Disposable< Matrix > correlation () const

Protected Attributes

std::vector< boost::shared_ptr<
StochasticProcess1D > > processes_

Matrix sqrtCorrelation_

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.

Disposable<Array> apply ( const Array & x0,

const Array & dx

) const [virtual]

applies a change to the asset value. By default, it returns $\mathrm{x} + \Delta \mathrm{x}$ .
Reimplemented from StochasticProcess.

Time time ( const Date & ) const [virtual]

returns the time value corresponding to the given date in the reference system of the stochastic process.

Note:
As a number of processes might not need this functionality, a default implementation is given which raises an exception.

Reimplemented from StochasticProcess.

QuantLib 0.3.11

Getting started

Reference manual

StochasticProcessArray Class Reference

Detailed Description

Public Member Functions

Protected Attributes

Member Function Documentation