QuantLib_HullWhiteProcess (3) - Linux Man Pages

QuantLib_HullWhiteProcess: Hull-White stochastic process.

NAME

QuantLib::HullWhiteProcess - Hull-White stochastic process.

SYNOPSIS


#include <ql/processes/hullwhiteprocess.hpp>

Inherits QuantLib::StochasticProcess1D.

Public Member Functions


HullWhiteProcess (const Handle< YieldTermStructure > &h, Real a, Real sigma)

StochasticProcess1D interface


Real x0 () const
returns the initial value of the state variable
Real drift (Time t, Real x) const
returns the drift part of the equation, i.e. $ mu(t, x_t) $
Real diffusion (Time t, Real x) const
returns the diffusion part of the equation, i.e. $ igma(t, x_t) $
Real expectation (Time t0, Real x0, Time dt) const

Real stdDeviation (Time t0, Real x0, Time dt) const

Real variance (Time t0, Real x0, Time dt) const

Real a () const

Real sigma () const

Real alpha (Time t) const

Protected Attributes


boost::shared_ptr< QuantLib::OrnsteinUhlenbeckProcess > process_

Handle< YieldTermStructure > h_

Real a_

Real sigma_

Detailed Description

Hull-White stochastic process.

Member Function Documentation

Real expectation (Time t0, Real x0, Time dt) const [virtual]

returns the expectation $ E(x_{t_0 + Delta t} | x_{t_0} = 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 StochasticProcess1D.

Real stdDeviation (Time t0, Real x0, Time dt) const [virtual]

returns the standard deviation $ S(x_{t_0 + Delta t} | x_{t_0} = 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 StochasticProcess1D.

Real variance (Time t0, Real x0, Time dt) const [virtual]

returns the variance $ V(x_{t_0 + Delta t} | x_{t_0} = 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 StochasticProcess1D.

Author

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