sqrtCorrelation_ (3) - Linux Manuals

sqrtCorrelation_: Array of correlated 1-D stochastic processes

NAME

QuantLib::StochasticProcessArray - Array of correlated 1-D stochastic processes

SYNOPSIS

#include <ql/processes/stochasticprocessarray.hpp>

Inherits QuantLib::StochasticProcess.

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

Disposable< Matrix > diffusion (Time t, const Array &x) const
returns the diffusion part of the equation, i.e. $ igma(t, mathrm{x}_t) $
Disposable< Matrix > covariance (Time t0, const Array &x0, Time dt) const

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

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

Disposable< Array > evolve (Time t0, const Array &x0, Time dt, const Array &dw) 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_

Detailed Description

Array of correlated 1-D stochastic processes

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> 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<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<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.

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

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) dot Delta mathrm{w} ] where $ E $ is the expectation and $ S $ the standard deviation.

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.

Author

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