StochasticProcessArray Class Reference

Array of correlated 1-D stochastic processes More...

#include <ql/processes/stochasticprocessarray.hpp>

Inheritance diagram for StochasticProcessArray:

Public Member Functions
	StochasticProcessArray (const std::vector< ext::shared_ptr< StochasticProcess1D > > &, const Matrix &correlation)
Size	size () const override
	returns the number of dimensions of the stochastic process
Array	initialValues () const override
	returns the initial values of the state variables
Array	drift (Time t, const Array &x) const override
	returns the drift part of the equation, i.e., \( \mu(t, \mathrm{x}_t) \)
Array	expectation (Time t0, const Array &x0, Time dt) const override
Matrix	diffusion (Time t, const Array &x) const override
	returns the diffusion part of the equation, i.e. \( \sigma(t, \mathrm{x}_t) \)
Matrix	covariance (Time t0, const Array &x0, Time dt) const override
Matrix	stdDeviation (Time t0, const Array &x0, Time dt) const override
Array	apply (const Array &x0, const Array &dx) const override
Array	evolve (Time t0, const Array &x0, Time dt, const Array &dw) const override
Time	time (const Date &) const override
const ext::shared_ptr< StochasticProcess1D > &	process (Size i) const
Matrix	correlation () const
Public Member Functions inherited from StochasticProcess
virtual Size	factors () const
	returns the number of independent factors of the process
void	update () override
Public Member Functions inherited from Observer
	Observer (const Observer &)
Observer &	operator= (const Observer &)
std::pair< iterator, bool >	registerWith (const ext::shared_ptr< Observable > &)
void	registerWithObservables (const ext::shared_ptr< Observer > &)
Size	unregisterWith (const ext::shared_ptr< Observable > &)
void	unregisterWithAll ()
virtual void	deepUpdate ()
Public Member Functions inherited from Observable
	Observable (const Observable &)
Observable &	operator= (const Observable &)
	Observable (Observable &&)=delete
Observable &	operator= (Observable &&)=delete
void	notifyObservers ()

Protected Attributes
std::vector< ext::shared_ptr< StochasticProcess1D > >	processes_
Matrix	sqrtCorrelation_
ext::shared_ptr< discretization >	discretization_

Additional Inherited Members
Public Types inherited from Observer
typedef set_type::iterator	iterator
	StochasticProcess (ext::shared_ptr< discretization >)

Detailed Description

Array of correlated 1-D stochastic processes

Member Function Documentation

size()

Size size ( ) const

overridevirtual

returns the number of dimensions of the stochastic process

Implements StochasticProcess.

initialValues()

Array initialValues ( ) const

overridevirtual

returns the initial values of the state variables

Implements StochasticProcess.

drift()

Array drift ( Time t, const Array & x ) const

overridevirtual

returns the drift part of the equation, i.e., \( \mu(t, \mathrm{x}_t) \)

Implements StochasticProcess.

expectation()

Array expectation ( Time t0, const Array & x0, Time dt ) const

overridevirtual

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.

diffusion()

Matrix diffusion ( Time t, const Array & x ) const

overridevirtual

returns the diffusion part of the equation, i.e. \( \sigma(t, \mathrm{x}_t) \)

Implements StochasticProcess.

covariance()

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

overridevirtual

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.

stdDeviation()

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

overridevirtual

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.

apply()

Array apply ( const Array & x0, const Array & dx ) const

overridevirtual

applies a change to the asset value. By default, it returns \( \mathrm{x} + \Delta \mathrm{x} \).

Reimplemented from StochasticProcess.

evolve()

Array evolve ( Time t0, const Array & x0, Time dt, const Array & dw ) const

overridevirtual

returns the asset value after a time interval \( \Delta t \) according to the given discretization. By default, it returns

\[E(\mathrm{x}_0,t_0,\Delta t) + S(\mathrm{x}_0,t_0,\Delta t) \cdot \Delta \mathrm{w} \]

where \( E \) is the expectation and \( S \) the standard deviation.

Reimplemented from StochasticProcess.

time()

Time time ( const Date & ) const

overridevirtual

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.