HullWhiteProcess (3) - Linux Manuals
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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