QuantLib::StochasticProcessArray

StochasticProcessArray Class Reference

#include <ql/Processes/stochasticprocessarray.hpp>

Inheritance diagram for StochasticProcessArray:

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List of all members.

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.

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